--- a
+++ b/Sentiment Predictor for Stress Detection.ipynb
@@ -0,0 +1,5751 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Using TensorFlow backend.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "        <script type=\"text/javascript\">\n",
+       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
+       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
+       "        if (typeof require !== 'undefined') {\n",
+       "        require.undef(\"plotly\");\n",
+       "        requirejs.config({\n",
+       "            paths: {\n",
+       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
+       "            }\n",
+       "        });\n",
+       "        require(['plotly'], function(Plotly) {\n",
+       "            window._Plotly = Plotly;\n",
+       "        });\n",
+       "        }\n",
+       "        </script>\n",
+       "        "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import random\n",
+    "import sys\n",
+    "\n",
+    "\n",
+    "## Package\n",
+    "import glob \n",
+    "import keras\n",
+    "import IPython.display as ipd\n",
+    "import librosa\n",
+    "import librosa.display\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import plotly.graph_objs as go\n",
+    "import plotly.offline as py\n",
+    "import plotly.tools as tls\n",
+    "import seaborn as sns\n",
+    "import scipy.io.wavfile\n",
+    "import tensorflow\n",
+    "py.init_notebook_mode(connected=True)\n",
+    "\n",
+    "\n",
+    "## Keras\n",
+    "from tensorflow.keras import regularizers\n",
+    "from tensorflow.keras.callbacks import ModelCheckpoint, LearningRateScheduler, EarlyStopping\n",
+    "from tensorflow.keras.callbacks import  History, ReduceLROnPlateau, CSVLogger\n",
+    "from tensorflow.keras.models import Model, Sequential\n",
+    "from tensorflow.keras.layers import Dense, Embedding, LSTM\n",
+    "from tensorflow.keras.layers import Input, Flatten, Dropout, Activation, BatchNormalization\n",
+    "from tensorflow.keras.layers import Conv1D, MaxPooling1D, AveragePooling1D\n",
+    "from tensorflow.keras.preprocessing import sequence\n",
+    "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
+    "from tensorflow.keras.preprocessing.text import Tokenizer\n",
+    "from keras.utils import np_utils\n",
+    "from tensorflow.keras.utils import to_categorical\n",
+    "\n",
+    "\n",
+    "## Sklearn\n",
+    "from sklearn.metrics import confusion_matrix\n",
+    "from sklearn.preprocessing import LabelEncoder\n",
+    "\n",
+    "\n",
+    "## Rest\n",
+    "from scipy.fftpack import fft\n",
+    "from scipy import signal\n",
+    "from scipy.io import wavfile\n",
+    "from tqdm import tqdm\n",
+    "\n",
+    "input_duration=3\n",
+    "# % pylab inline"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Reading the Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Actor_01', 'Actor_02', 'Actor_03', 'Actor_04', 'Actor_05', 'Actor_06', 'Actor_07', 'Actor_08', 'Actor_09', 'Actor_10', 'Actor_11', 'Actor_12', 'Actor_13', 'Actor_14', 'Actor_15', 'Actor_16', 'Actor_17', 'Actor_18', 'Actor_19', 'Actor_20', 'Actor_21', 'Actor_22', 'Actor_23', 'Actor_24']\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Data Directory\n",
+    "# Please edit according to your directory change.\n",
+    "dir_list = os.listdir('E:\\\\8th sem\\\\Final_Year_Project_Files\\\\Audio_Speech_Actors_01-24')\n",
+    "dir_list.sort()\n",
+    "print (dir_list)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create DataFrame for Data intel\n",
+    "data_df = pd.DataFrame(columns=['path', 'source', 'actor', 'gender',\n",
+    "                                'intensity', 'statement', 'repetition', 'emotion'])\n",
+    "count = 0\n",
+    "for i in dir_list:\n",
+    "    file_list = os.listdir('E:\\\\8th sem\\\\Final_Year_Project_Files\\\\Audio_Speech_Actors_01-24\\\\' + i)\n",
+    "    for f in file_list:\n",
+    "        nm = f.split('.')[0].split('-')\n",
+    "        path = 'E:\\\\8th sem\\\\Final_Year_Project_Files\\\\Audio_Speech_Actors_01-24\\\\' + i + '\\\\' + f\n",
+    "        src = int(nm[1])\n",
+    "        actor = int(nm[-1])\n",
+    "        emotion = int(nm[2])\n",
+    "        \n",
+    "        if int(actor)%2 == 0:\n",
+    "            gender = \"female\"\n",
+    "        else:\n",
+    "            gender = \"male\"\n",
+    "        \n",
+    "        if nm[3] == '01':\n",
+    "            intensity = 0\n",
+    "        else:\n",
+    "            intensity = 1\n",
+    "        \n",
+    "        if nm[4] == '01':\n",
+    "            statement = 0\n",
+    "        else:\n",
+    "            statement = 1\n",
+    "        \n",
+    "        if nm[5] == '01':\n",
+    "            repeat = 0\n",
+    "        else:\n",
+    "            repeat = 1\n",
+    "            \n",
+    "        data_df.loc[count] = [path, src, actor, gender, intensity, statement, repeat, emotion]\n",
+    "        count += 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1440\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>path</th>\n",
+       "      <th>source</th>\n",
+       "      <th>actor</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>intensity</th>\n",
+       "      <th>statement</th>\n",
+       "      <th>repetition</th>\n",
+       "      <th>emotion</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                 path source actor gender  \\\n",
+       "0   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "1   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "2   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "3   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "4   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "5   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "6   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "7   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "8   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "9   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "10  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "11  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "12  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "13  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "14  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "15  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "16  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "17  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "18  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "19  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "20  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "21  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "22  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "23  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "24  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "\n",
+       "   intensity statement repetition emotion  \n",
+       "0          0         0          0       1  \n",
+       "1          0         0          1       1  \n",
+       "2          0         1          0       1  \n",
+       "3          0         1          1       1  \n",
+       "4          0         0          0       2  \n",
+       "5          0         0          1       2  \n",
+       "6          0         1          0       2  \n",
+       "7          0         1          1       2  \n",
+       "8          1         0          0       2  \n",
+       "9          1         0          1       2  \n",
+       "10         1         1          0       2  \n",
+       "11         1         1          1       2  \n",
+       "12         0         0          0       3  \n",
+       "13         0         0          1       3  \n",
+       "14         0         1          0       3  \n",
+       "15         0         1          1       3  \n",
+       "16         1         0          0       3  \n",
+       "17         1         0          1       3  \n",
+       "18         1         1          0       3  \n",
+       "19         1         1          1       3  \n",
+       "20         0         0          0       4  \n",
+       "21         0         0          1       4  \n",
+       "22         0         1          0       4  \n",
+       "23         0         1          1       4  \n",
+       "24         1         0          0       4  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print (len(data_df))\n",
+    "data_df.head(25)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plotting the audio file's waveform and its spectrogram"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "E:\\8th sem\\Final_Year_Project_Files\\Audio_Speech_Actors_01-24\\Actor_18\\03-01-01-01-01-02-18.wav\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(22050, array([0., 0., 0., ..., 0., 0., 0.], dtype=float32))"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "filename = data_df.path[1021]\n",
+    "print (filename)\n",
+    "\n",
+    "samples, sample_rate = librosa.load(filename)\n",
+    "sample_rate, samples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(77989, 22050)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(samples), sample_rate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def log_specgram(audio, sample_rate, window_size=20,\n",
+    "                 step_size=10, eps=1e-10):\n",
+    "    nperseg = int(round(window_size * sample_rate / 1e3))\n",
+    "    noverlap = int(round(step_size * sample_rate / 1e3))\n",
+    "    freqs, times, spec = signal.spectrogram(audio,\n",
+    "                                    fs=sample_rate,\n",
+    "                                    window='hann',\n",
+    "                                    nperseg=nperseg,\n",
+    "                                    noverlap=noverlap,\n",
+    "                                    detrend=False)\n",
+    "    return freqs, times, np.log(spec.T.astype(np.float32) + eps)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.28273218017925605"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sample_rate/ len(samples)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 0, 'Seconds')"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1008x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plotting Wave Form and Spectrogram\n",
+    "freqs, times, spectrogram = log_specgram(samples, sample_rate)\n",
+    "\n",
+    "fig = plt.figure(figsize=(14, 8))\n",
+    "ax1 = fig.add_subplot(211)\n",
+    "ax1.set_title('Raw wave of ' + filename)\n",
+    "ax1.set_ylabel('Amplitude')\n",
+    "librosa.display.waveplot(samples, sr=sample_rate)\n",
+    "\n",
+    "ax2 = fig.add_subplot(212)\n",
+    "ax2.imshow(spectrogram.T, aspect='auto', origin='lower', \n",
+    "           extent=[times.min(), times.max(), freqs.min(), freqs.max()])\n",
+    "ax2.set_yticks(freqs[::16])\n",
+    "ax2.set_xticks(times[::16])\n",
+    "ax2.set_title('Spectrogram of ' + filename)\n",
+    "ax2.set_ylabel('Freqs in Hz')\n",
+    "ax2.set_xlabel('Seconds')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mean = np.mean(spectrogram, axis=0)\n",
+    "std = np.std(spectrogram, axis=0)\n",
+    "spectrogram = (spectrogram - mean) / std"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([-1.9141038e-07, -4.1607140e-07,  2.0688096e-06, ...,\n",
+       "         5.6699279e-05,  2.1195672e-05,  3.1794041e-06], dtype=float32),\n",
+       " array([20992, 58880]))"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Trim the silence voice\n",
+    "aa , bb = librosa.effects.trim(samples, top_db=30)\n",
+    "aa, bb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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/KF7cCGXuaN1/XwJdMBSXe144AQCWRJ7OzEDn2KgNcmSdU3tsxcMHTYkLTHV2ou6Soqxc7GrjqLoDlCflXIm8c3fM+uvHwQD19/41/5iL3YgamTxEQs2gaoCa1xOTSKkQgs5tiRh608LAHozEOofehLf65/xzDLW4QEUKaWiDYiAcIzGVwT2AbFBkZGRkZGRkZGRkZDwq5KTs/Y2W8Pz3ImpCIooR8TCf6/iTLBD5ZiDG2lauTmBDULyGAfpNV3jmljvaW9EWgZBOwFnRF+6ulQDvZcN85aOe+cloAGvDO9z2iJd6u1B0BNASpp3Atc4kX9kkovK0KqILjYDK0zr+czsbUF5TdKRI1GdDRH1qOxABbQdomV3hUW2JeQ4wKHyln8gcawmP6ihp73Ff0DzWAtHc7sh/90em14bZkj8P1wK8TEWdidxThUjVFkXNi8xTRctVkSXQ0aWOmD+g3/1qoSNHi13fKx+pZaFUnCISuGrvqZT5ikDit5LRHY70ut8VUY5a1RcwAC07nQI1Sq7/7IRMecrIyMjIyMjIyMjIeLRICQsYxXsdj1mD4nDD9xLMV7Wnqi289spTDtp7o/jcACsiiaIT4H12R773pjXU3p2m4I5GoDxVquYGQFO4/msBGdRT6/71nuKjso+V/p1u+5Tw7EU44S3xbFXSJWh9/ylR9Rl03kqkeux62n5RQ3WayPvUF52ca2vvX1lIHdYDXtuuWIIskGQ6EDkDLbQc58WRH6GoiyJcAOdKF9z2itD/B5gZ+UmkA9PPpWO+cEQ1EAVT0YNInobk6otICugcibPm33OAT6z58qJKXh1gUeSkrfQDdSjMr4mwHriWJJKyK6JAI+gaIwuiGCnoCEQvUNenJMRJVEHcCAYiAlEEIgMmvh2RPIyi8I+JCAPsCeQIxV6GuZsYRTVaEDUEADpCTmixqyeQ2hCqED1oBZXIRiyJTUGjrI0FtcHpjrZfQ0JtskBTVgJiQcyZSDazQI0IsQ4qWl0rQFXrigpYEaUxlawYSZhVm6wIhaPb8+fYhvmJ8gAD/M3LfE2Poykm4Upf3w+l9BJ5LsoRMBewrjvDwAsjoDbqG6Y3DWdHH3PbI5u9RsnfzCkjDqAt6hncxJNkH/IcgTW7EM9fGdcAbfE+rHJW9nHjlF//4VCg6PNaXxjg6CKga8kf68bAp9aArpReK+vCdgdEUcKGaYOzLtbTdqA+1ZRIyi4VPpVovaSpRuvpjH8OQe0DKCEU4IRyH8Bw5B9TBJKyRyM9x64pEjujPHCdYx8bFBkZGRkZGRkZGRnXEjmHYo8juaEypVkeSYauCI98pIbEeSGptxEIO6oQ6oxpbXVFz2oP9VRRTujVQB0KlWi60dfev7647xEa0Cq+1/VoukP2cVhILs4L2dim0N0H7enuFgFvqQgpVwIVZiMylwqqnsE8usz1Mn5dBVV/BqAvbvtiX7+TyksZifqsj/zzrHb0tZwq+1SS9khXwy3sZr89kHCvIhDDgNb8hcHfue2Nqk/NAqiKBNBINWX17QgEpllNPvVqtaSpaD0RobBIortYHiIRYSX6sWS+JxygNfApTaUATdWS/06NAnPs4eFfu+3Diq6kfqQ47LYP0B73mnh2ZSE9q+oCgX4XIlD0rogYh6mIjaCy7Qlklaftw8xeCXwH49v5N8C3Al8F/BjwWcBzUkr3To6tAb8EPBsogFeklN5lZlPA/wAeB4yA300p/eB2x6ZoMTOViLqF366UkwCKDf88qyVdun4gDIq5pJVt1gXNtRCcToBa2X/x6wHFEFWE73RP017WBAUjsmnolfyPz7rpEGt75IfPVUHCCHf0TLHitkeuVSKwniuFlQ3TBdSU+MlU0gbFSHysI5zwplC+WexpKsCyMDqagQ++CQv9QoBX3ir8olGlAE2oIzaufZGXADAY+ccUSfPsFfWhP9KKVbWSP4ciKk+R3CYFRSNro9d9dc8ihp5SxioCuU9nez49qyecM6ALpHlFai9BzeVC0CEBBoU/T8+MPiL76FRuddtrSW/k20I1b2j+u7A20nS3Vs+nkZVDNSRE/oO4nxB79/cFdqCe0/WOiLLco4KZ3Qx8H/DslNJTgTLwEuBvgX8G/Ollf/IygJTS04AXAf/ZPrXKvDal9GTgGcDzzezLdmvcGRkZGRkZGRkZGTuClGA4iv23h7HblKcK0DSzATAFnE4pfQyu6H17CvDHACml82a2wtgY+Svgf09+3zezDwC+NAUAJVffWOSyhvJnlDWmKswCzFTEIwjMr5nk60lHKnMqZZJRIEIxCtTuUFAssUhi7rqgC0Q8RNPCQwQHZR9Twgmt6phE5s+UuJaZQGJdTdRLWajpZaI19CktnaFWR+nsQEXUbvIjA7OByONM1T8mkgzdF6pp0wFlgJaoIFsJLN/N0gF5jMKhkZ/g2Q3UKVnkk257xAPdqPpzqD/UEQqV3Nup3S77GBX+u68SrkHT++roqPKqSGRe652UfZzlGW77XIDqusya277e15QnpdAUQankrx+VwFpYFu9Ud+BHhAEWBbWqWQkkTItoy0h49dt9Hb0cFaKWhahPBGBinPs/DTmKnEOxLaSUTpnZa4GHgQ7whymlP3T+5EPA3Wb268CtwLMm//+rSweY2QJjytTr9AgKCifcpqRWB4KPCTBV9vuoC+oEaNnYdqGpIop+c7DwDQ7QUqsRhaaO+PgMAkZJVdyPQ+hr2Ug+XWAmcj+EVOpMgEZ2pO5/JOeq/gdwtqrv+a0N3/A5JOSRAZSgWSQXSCmeDQp9La2B/3E63tbhc6XCElH4UvvBkBSveHaRe6oMvRvERh+gLeZ6x/Sm4WjVN1q7Iy0FdLZ8xG2vVvT7NJXm3PYFoQIF0BeUuAcLn0MPmuLVMK0mtBMYig1ftawdJ0874NNaFmoBlbiVo257254l++gKWlQn6ZyS6ZKfu3DH6HGyD5WbcKKqjbQLo/vd9kGhnWJd8WyV5GtHFJwDXVCuUtbv5ChQ/G67iEiO7wnD5TFgUOwm5ekAcDdwJ3ATMG1m/8L5kzcAJ4F7gZ8B3gufWv3NrAL8GvCzKaUrurvM7DvN7F4zu3dnriIjIyMjIyMjIyPjUSKBFUXov72M3aQ8fQnwYErpAoCZ/Tbw+cBbrnRwSmkIvPLSz2b2XuATmw65B/hESulntjphSumeyXGYlZKX6HX7jO9BXBDeY4C+oPgoxSLQijE3JD+xF+Cg8CTM1CPRBaGLLugXAI2yP53WBwEvtRiH8iABVEV0oR/wynaFF3Km0AnCRdJJbduFiuhMi8jT+Bh1zwNeSvFYBgE63ECspTNCmx206tUZHeSgKRSYWsOASot4LhH1HEWLOdrQkYH+yI/YtIbai63on4MAXUUlzFaTvpabkh/lOBy4Hz3BdV0qfEUrgIagQ0aSoZUSkFJeA+gIwY5eoAbArKD3qbUB9Fyvo+eYWrOrJb2WHh3d6LbfMa097gqDln8OgJXSabe9Lwq5AdTLfjRORSjKAQWnkUiYHgy1MMA4NdZBYA7WKtunZfYH/j2/9kg69L0PsJsGxcPAP5ioNHWAL2YcfbgiJsdZSqllZi8Chimlj07a/j0wz1gxakegWAspQM/pCpqHUtCI4LaGpudEivApqKEerGklhoW6bxytCErLGP4CNa1yToCpvv/BrwWmfV/w+auBPlThur6Qy1MbbNCFETsBo1aFlCMV31Ux9m6AJnS+owpT6Xl+VEiviVMAuijdykDLxk4JmUtlCII2jpoB/ta8oI03B7qPMx1/87IopHoB5vGNgR7a0jtrQuK2pylgPWH8NEqarnRz8ik+y0nncigluoHpOVYVxTdLgQrmyhFQDaTFKRndyLNVNLJ+0jShUyV/ns53niL7UEb8cknnUNSEAdUeRfIbfKeXrAoeoCs1av77Eslr6g18o2M4CihrCclgAop4ewJ7PPoQwW7mUPylmf0W8AHG1KW/Bu4xs68Gfg44AvyemX0wpfSlwFHgnWZWAKeAbwQws1uAHwH+DvjAJJn751NKv7xbY8/IyMjIyMjIyMjYNi6pPO1z7KrKU0rpR4EfvezXvzP57/JjjwNPusLvT0IgK+fTz+5a2Kfb/sOdCnj/eiJC0VFuWzRdYGOgJ2FZqAEFGE/UI5X8BLqCFhWhPG2IUMnZvg4Xr5b8JHUVXgdome+Jekp6suxD1TNQVKKI3v2scDEqDzXAxa5/opOt7euEdwsdGlB0trum9XO7TTiY1wZ6np9u+/cjQvF5uPCTSA8WugjbsZpP84isLy0xhyLry3TZ93SXC50M/VE+6ravB3Tzy4I2dTZAh+wLZZs77fNkHw1RcLI01ONoi7osbXQS8lTyqSKR+g8fXvLn0Fwg+v2xNf883ZIex/rQf/6jgOKQogH9VVVHBkoirbQ38hWtADoD/9mp2g0ASag4KXWlIpD4XRLFJiWdCT1OAvQ/WW9pB9T/rjlyYbuMjIyMjIyMjIyMjG0hGxT7FztRh0IhIg3ZEElL7YBnd9DzL2Y2kHdwpCm8boEARrUkvF2BRPeZqu9SP1bVHOfywE+cO1M6Jfsw4alSsqAADSEr3BD362BAslF53KcCb3hTHKMiYADdwvd0Lwe8pfOiEvaymOcAVSG1OieSUAEeP6vEFnTC44nhcbe9XOgHc4P5EYrIGrXY87n4F0UNAYCbd6CWRT/5z78ivaW6inGkDoWqRTAj689oOefOSCcQ90TtoFKAN94VeRj9kX7n1gb+mlwX0SmA2bJYs0e3yT6GZT8CsdbXcq1DUY19o9D1MFTF7kh0wcQ3vV7V0UlVFV7JtaZHQ+q4fAwjnRslowsZE+Sk7D0Ov7BdV1gUamMCcKiu6lAEVJ56/oK92Nc6z20VDg5sgA4n9ZHU90MpCkUWOXWWyCbqQumi294gYJSIDd9KP5BsJvooCQUVlTAJuhCgMpxBJ1SvDDXdYEVQOBSVAGBaqIRF8Mk1/7k8aUFvkERed6goXX3gJ0Wum6a0fKLnP9xGQEVsseQnMi+nE7KPUeHr9yv6DsBK72G3PWJQ9Ee+waA2gxFUBZ0JtKOoGZjHqr7QIKBEpxC5H0ca/vtwuKHXbEVlXRd1gQAqgoZaDsyPurjtEfUttU4l4SQCGI58ulG5pIVWipFvUJSEYTwKOCwUSqE6FNt/Jytl38BSxtV4HD7N+ZpjlyhPZvZk4FeAZwI/klJ67aa2FzOu2VYGfjml9OpAfxsppRkzuwP4GHAf45SDFvCtKaX7vL/ftToUGRkZGRkZGRkZGY95FCn239VhCfg+4LWbf2lmZeD1wJcBTwG+3sy0zNkj8UBK6ekppc8F3gj8sPqDfRyhSG7C0DHBBZkO3Bkl8R/Jc64KOkkP7Qlvm+8RGQo6CsDTRQLokYb2mM3V/WPWA7KxivIUkco81BVyeAFPVU0kva0nHTla6vvJqtWSv3goWWKAlnDezAaUekXpD2oB+sXIRIheD4OhWEyXA1GhZZGMeKir6QbrgkYWqditElFHMpkRLhZXrN95VRiJ6NKw0PKkszVfJrWwABVNVG2OSFSqYyKeTOXprgZ8bBXB/4xEt9cLP0G4G6gBMFP2n4sFkmqb4iMVoe3ugJ4HQ/x5GolQKErcIECJKwm55wgU5WkgvPqg53pJnKNS1lEQda2Rd7KQ8rYByvbwOo8u7ARSgkD9oqvvNp0HzpvZV1zW9Bzg/ktFoM3s1xkXmn6EOoaZ3Qm8lbEt8AfOqeZAK0Xsc4Ni6we4IUT+uwGKj9rwLetvNRf6/gu5WNLKFGWhN34UzYHuCEmhUoAr2aj4L8xCTd+QgzV/4/FwgM/fwz/PAdOUpxmZd6Llk25o+JvGAzX/fl3s6ddT13+IqJX5nUR09S+aT2mZFXUIQG/UIrVhlGHTVdYTulBXZQf4yd0ADUQhsoGulfy8lEaAIz8l+P598b6BLmzXHvg0RYBqxX9vy4EiWmpjOgg4G3pirewE5CEHwvCNOD1UnlfD/OJoAHM1Rd/S74uq3RChb6n7UTFtUNTK/vyoBzbZSk2qK+ouRLATxvMo+e/cThhGscJ2PmI0RP8YpWgFUAgK4XWBePThsJltrtl2z6Ro89XgZmAzn/Uk8NwrHPc64BdTSm8yszJtlMIAACAASURBVO+9rO1xZvZBYBaY2uLvH4F9bFBkZGRkZGRkZGRkXEskCBiSE1xMKT17mye8kpV/JYvm+cDXTP79ZuA1m9oeSCk9HcDMvg64B3ixd9LHrEGhNNwjNROGImv/QkdbpF3haWgHkjdn8UPfjYC3QoWt+4W+HyXhzWpUtOdOvXJTimcGLIgKsu0A3WQg5oeqEQBwQERkFmq+N+xATUdBauLZLvb0HFwRlaEjCdUqqbIbUHnqiETEaoB6VU2+N2smoKs/IxxiC4KWB1Ae+Z2EqtAKlRVVTRfARGb/bEDB6UZ8CqGqPg2wUlE0RN1Ho+yPtQi8192hX19mQ1RsBmgN/LneLvQ4IgnCCgNRgVpFMAD6wmsqlgZAV3Qvpe2nakbmR+R6FYqAqqJCVSQzR6JPI0FFVInf1ZJOqFbQdSqgEInGJr7F4z78aykElW1PILEj0qGTKMLLJj9+eUrp9BaHngRu3fTzLcBWx0YG9nbGyd8uHrMGhebB6nusqA8L+n3k2NAP0y6ODgfG4T/GWlkvtKqI2qDQfbS6/kZrsas34UoGdaWvF3y1wRlFGP3qfgQk4BTdqCeMtEGhjSe1IbAARUxBURoARiLXZxgoTHUBP8TeLPT8mRLUiKlAkUdFeYpgIHJsIlQAReEohNILaKNjVNabX/X8I/MjiXdSUaJA02IsYHAqytMJ8wvwAbSHt7vtrbJvtACMBv5z6Q0jBdR87vl07ZjsQ831COVpWhitC339DRuKedgRhSIBuoV/3yNG/EjQCFXuAkC94lPNVK4HBKh5Qr621Tkuz6HWIE8l8xJUYTv13o+P2QeF6yLYAZWnlNLrGSdbK7wPeMIkR+IU8BLgG65w3HsmbW8BXur09wLgAXXSx6xBkZGRkZGRkZGRkbGr2KEIxeUwsxuAexknTRdm9q+Ap6SU1szs5cA7GcvGviGl9JErdPEK4K1m9grgbZe1XcqhMKAPfIcazz42KMxVW2iJxLmpivZ2Ha37lvVKTfex2PW9BKOR9iDuBJRTdraqEy+nG/4x033thVSFx6o74D0uQhE+f36c6/veUoCTHd/D3BNRnws9PX/W+v44awEJlpWB/9zOlP2Ea0BGdKYC1JokPDg903OwLOqpzFT1/VBzcCZQIGR26FN8CtPvtVK+qQRoDX3h6e4Xmop2X9l3TLW1+AcX2x932yslHX1SEQhV2AygLKI6qtYFQL/qnydCEWz1z/t9BDzhKoI1CBS2Wx/4cz1S1HJ94K9BZ0vHZR/dwo9OqmgMQEUoiUUocZ2eP5fV/IGdUZtS0YOyfF8ikQGR+B14FzS0V74s5nEEo9H2E8h3FwkCYg1X3WtKZxnTma7U9g7gHeLvHwSet+lXr578/jigQ1SXYR8bFBkZGRkZGRkZGRnXEImrScres9jHBoUvG7tQ8y+9FzAmT3V8j1l7GOEW++21gJGoEvwiMoYV4RGLUPGT4PyXTEcGpgRn93BDe/+We74XqQiEHuvifpQDvPGGyMOpivsRWX4G4lpUrhDo6pZKlhigbr48aUUkSwMMheTrmmkv5dTI57ffMa3fhfmqf0xXJFwDXOze6LafKfR7fVpU5W2P/CrYAJ2B73EdBhK7pxp+tKUaWKNm6zeJcejogvLaVss6ytEX3uHD9SfIPm4rHu+2q+rkAIihRnKOlCRwBKIck1yPAZoiR29uqCWjh0JaNiKDKqVlA9Kzg4qf+6SiQqDzX0aFrmFUEYndFTHXI/dL5WEEyqlISddIpC2SpL738aiK1u057GODwsdds/7bctd0oNy70MVfCihFbQz9cRzoaarIuvlqMOXApjIJzko5ULyqLDZARaCOQFkaHbqPpqCrtft6payKzcuBmt5U3tT0PxzzQgVqqa9fT1WgsROou1AW11pLesPYMf8j2kNTxBr4H+tG0huotlDp6Y50H1OCJjYMzOPVkUi6LekNo/rQ7oSqzVz9itHyR+Bp9tlue0CfgIfKvlHSquhE5lbh16pQCbUAtZr//G8q7pJ93Fr36xk0+poW0y75FI0NUfgO9AY64ghQBVynK5GkbCFO0vELfAKsiXpLsaR9/92PFMdTRmnEoIjVXvBRKvnX2x/63/wiULBSjdMCBpguNhlY58R7q4rn7RlkgyIjIyMjIyMjIyMj41EhsSMqT9c7HrMGhXLaz1T0w1fO30iEQuTUyqrPsDOeSoVIlWIVgeiO9P040faPWQsIo6+JJONIUvZIeF42RCIiaKld1a4iYABD4fVoqVLawKrw7FUC4fOhkEmN6O5Xk+/ZrYtaFwBDkYx4vKXv6fme7x18cF0/+56Q0R0E3uv20KfOtPu6unSt4nvTI8nyU2X/nVR1CADqQ0HR4KDso2Z+pExFyQAGyY+UHQjo5h+oq/dWRyhKYi2MVP1WaBWaevXwhv/s2gGK6VJXUBVL269iHIlQ9EeKahSo2yK89qqOCQSSnQPRg454twshphCRyFX3NJLE7gnfjMfxGJGEjSBHKPYyzF0cVH2rQWAz1xZ0pU7gXVoWyRp19MdJUiMC+Q8RNQ+FqihcN13dgaJBAfpWs+xPa1W0DmAojI6IUaLmkDIouoE6FKp+SAps9soIZaQiQDUq+xvXIqA6cjj5+u2Klge6+N1dM7qPRkmoTQUM4wtdf/PbTTpnYL7i05F2gp8cocUoqDwegFWRV1BN2lisX73oyKehJpSxDgWojIca/nvZD9TsmW37BtQooAJWFhtClZcA2rEWEdXbgU8HM6p4omnFqqFwfESMErWJ3onCd3Vh5IPOgRiO/HkcydNQBeMssAcyRUEO0L9UHkalrClz/cFWNduuE6TdUXm63rCPDYqMjIyMjIyMjIyMa4xIstkex741KIwylfLClu1KvWKqrK1J5ZiL6NXfNec/gnpLe4c3BkJ/O1R3wYeq6gzQ64nIQMBzp5KyFwPyW62R70WKVI9W1X/XRzps3S8CpdIdHKzpa33SvH/PP76qn9tAVKDuBrxy1dGtbvtMQL/9xmnfU9UOJJgrKtqhmr6WA+KY9kirCS33/WNGG5pqtGo+7aESSDLtCRpIKUU8iH57JLp5YORXSy4n/SlaE4nMR4sbZB8Kx5r6ftzS9OeYUj0CuND1q1gvDbVXVgkQRKIcikIaebbne743/JzJArsyMhChGilaZa2sIxRKOauXNK1OiQOohGrQlKV61Z8fZfMjPgCtnp8IP0TXdkiCvhWJKiPoocPrvsZEALtU2O56w741KBIjhqOtFyFFR9FqQzAvKDyRPhCUg+4oEk/2N42VQIqFKnDUHQY2poIKUgosLofqSmp1+zKoO5EadWtTc60P1vwPraKAVXp6pHNChaVZCcjbig1QrayNAVUc73BDf8wP1P2xRgxBlVMS+cANBdUsQodUlMppQcsDuHF4m9u+UvIpYgAXy59021uBonQrff+D3xA5FgA3lrZ27gA0A4tUCX8T1QjM9fMd/1qWe3p+LIu8gvVBpHii//xHAQpYZSTGIaScAW6Z8Z/dIf3q0xX0mwvdO2UfrZJvMFQDRRxHyigZ6bm+LgroTVV9wxhgtuw7C1pC0Qq09GxRiE14gFKp8hsiVCNldFik9oLKwwjQt65/ZNnYjIyMjIyMjIyMjIztIKs87WWUKDnhS0V5mq5oasR01fcSzI307e0Ir35/Snv/VFj6fEdbxoretzbQHuYZUVCuNdR9qHEE2AQ0REJbhK7UFio8x5o6QfRAXRRJEknswwAdRSVlR6BUepaHAXqX8A5WS4GiY4Lh1Q9c7IG6/77MisJVoAswRsQWlBhZNVA1qi6il8cKXTBsVBJeW3Sy63zVH8d0gNo5I2oViNIfANREhnArQIkbCo/pJ1r6fvQLvxZBhCakImXTopYOaFrmwdFR2ccTZ/37EaFdDkXRyk+2Nb1vVPJfql5gnqok9emKvh9Tol5KLRD1UeOoVXW0pVv2Pf9VoUbWQI9T1QZaG+lE556g5u2Eslakfsha6yPymGuKTHnKyMjIyMjIyMjIyHjUSAkC6pJ7HfvYoEgkx2uqfEiRBOKVnm85R+QDldEaqTBxSBjwGwFO79rAn+wR3nhXRGRWB3q6qfM0tOMOlTY3QLuYVwSnt1/4nHDQ90NJMkYcGi2RYyMKaQOav66quQMgvHIqPwKgIdzUayLPB6ArohgdwTsHmBIV35uBe3qgpuZxxAPtR3Uicp3Dnp+oPArI+d4qePazAeVZVVNFLD+TPvxnG5E4namIdzKQszYt3pf1wMXMiSSbyLp/UbwOUwFRCBWprwbyAFXgsB6QN24k3+PeFjVIIugGEqpnS34UYyQSiAEayY8OTCddbXtNXG9T9FEObO1UpfWirK9V9bHRPyf7aPfOuO0pUG17LyDlCMVehm9QqEcbMQaU0dEK6NWvi83aqn6nScI8GuwAd+9EW+8a9KZBf6zVt7gS2DXM1fz7XvT1x6msqGgBSenhNgvbRdafabEhWA9Qa5SW+CCQxj5T8udHhAZSEZuXqUDS7YWO/2DUuxJBZPOr6DcRqtqNgu6oaEQAU21/c3O6rT/W6r7XSts39FRRzAg2AgbnxlAo8KSAipygbiphAIBp8eVV7QAmaq6sBBxJiiW2Ez7VRkl/B+dG/jxtB6hGI/OfrarJAlptrBoorjlX+DQgRWUEqAoa2ZTYyC+jlaS6oraHUqsCrb7VFUnuY6g6WhGqtKblXnNk2diMjIyMjIyMjIyMjEeFnEOx15FcWbRzXd97M1fRVrFylq8MtGfmfE95sWUXdISb6WJXexpqItu5KTzhACbiPhsB6dkjdf+CUyBR+XzXP6YqvOkA9b6IPgX4kA+3fMqKqnfQENQbgFnh2T0fqFR6tKloUzqJMFIjQkH1EMj9ZV4kZU8HwvgzQs63EXgXVLQugsMij322oudHa+iPY6mn30kVXQgEjuiL6ORyX9/TjnjnVDvoZOhhwIs9EodEJHBVxK4aiPoo+qesYoymAEbWfRX1i0Qn6yLaMpc0xbRe+KIgkWeroCIDALNi7xCJYPWSkmDfPlR1+pYQ2gDoDv3k8SKQlF0q+YwBC1xtUbTkMdcc2aDYv1D1HSIbAjU9IvNHbcIji7FaJlWdAYCWKAs/CGzkFSIfSYWjDf1RUNd7QRhxAGuC06T4/gC3T/ta4AeavuLQyXUd5r/QU3VM9D1fFZs5VfwKAkpRvUgOhd++Eth0KqwE8ngUVfFsZ/sFGnci+t0NUAgVNU/VQwC4b8XfWChnBMCCyBmIrJVqoz4IdDIQKk8bpjcm5/r+/DhW04pmyiiNqF4ph1Yl4ExYqPoT5GBNbypvEC/uYEEXs5gWm/AzbU1TPdP2HQHq2YOmB982o5+typ+K4HTbfy7LPf9aI3SlDRbddlUUE/Rmv1HTSnSFGOtgqBW+rnukXIciIyMjIyMjIyMjI2MbSFnlaS/D3JDvQVGReVrUCADoinBxxIOoEpX7AatWeXaPNDWtoRCFNRVlAaAlKE1LgkYEO6OsphymEUeBOqYXSMruFyKxW9yvdiCpf01QWiLJ4y2RzBrx/K6PfE+mBSIUSj0nQjNTtQraAZWn+ZJ/02ZEdXIAkRseSso+L0pmzAS4RuqenenquhynzFdhOdT3tfvH8KNto8Aci1CJFFSNmq7Q5gdYFkNtBqJgy33fa6+U+wAqIno9U9Xrx7yopTRd0RGK6bJ/LRHKinofIu+Lut5qIDl8WggdzAWEEBQi1dhVzR1FXJgRtVIANkp+8ni/pCMDzZpfY6RenpN9DAUtah1dD2M0iiR/X0PsUg6Fmb0UeNXkxw3gu1NKH5q0vRh4HVAGfjml9OpAfxsppRkzuwP4GHAfY1HUFvCtKaX7vL/f3wZFSYdat0KE8qSOiSyCQ8F9iCjbqH2WKtQFmpPZ2AG6UjewudUflsCCLs7TCzyYstiYzgY+LI1yoAKaA2WwQsDwCRhoygBrBDYEXaFY1VfEczTdYC1QYO9g1d+JzQaMgemyP4FqZZ2D0xSclanAOBYF/XgpsDFReQUXWZZ9qA1hhJu+2PcNF7XRB5hWBbACFJ+qOKZeaErLjJLsDCjRBV4HibqSfA2M41Ddn2SKlgmwJOTThyIfAKAjXu2dcCZEpKt3onjiubY/1rM94b0DCkGF7gn52mpga1dLPo1sFMihGBZqTda0qaIQOWsV3/AB6O4FZdndoTw9CHxhSmnZzL4MuAd4ro0l4F4PvAg4CbzPzN6eUvroVfT9QErp6QBm9l3ADwPf7P3BPjYoMjIyMjIyMjIyMq4hdimHIqX03k0//gVwy+TfzwHuTyl9EsDMfh24G3iEQWFmdwJvZWwL/IFzqjnQ3qddNygmltK9wKmU0lea2UHgN4A7gOPAP59YVzXgl4BnM84zfkVK6V2TPmrAzwMvnLT9SErpbf55y1TKW1u296/5D3dWFEACOFL3Leu5gId5VdCAIiobCAdQpPBUa6ASmSPeru2P44xw3ih6DoAoQxHz2ovLjUSfVgWtQdWhiEQoLgrPTD3AEqmKg5YDN+xw3b/WuUCi4lLXP8+5QIRivuYrUh2oaY9rU0SWpsuajzIQc309UCPgogjpKVoEwAURGVgra6rAU3mS214E1qiVkf9iNwKfIqVaFFEBUwnkUyOtaDZX8p9/pOCgQqSAp9qfRAQ9uoJW2VETGS1iEFEqPN/xD1rua295u/CPKbUCEQqhNlWK3FPhcV8xXSNC1aFI5t+vUaB4a8f86MFQ8aCB3sBXeWqN9LUqJahIHYo9gbgSx2Ezu3fTz/eklO4J/N23A78/+ffNwIlNbSeB517hb14H/GJK6U1m9r2XtT3OzD4IzAJTW/z9I/CZiFC8gjEX6xKZ7geBP04pvdrMfnDy86uAlwGklJ5mZkeB3zezz0spFcCPAOdTSk80sxJwUJ00pYKRIyWmvsWqyBZAreS/1BGq0Xxt+1arMjrqAbqSqtw6H3inj9YDnCYJf0qeDClnbR/q3Y+E4OtC9rUhqDURqBD9WiBEr2y0iGNFGWARmtlA3PR2SSvwrPZn/T4C0sVKoSmCQzW1Nujd7wPC6bE60JssRY2YSprj3BC5C90Af6dnvjF4pKQ53zuQQiGpdxFZ0KNNfzEM5Wip9kAfitHUDNBlVZ5XK5APsiRUrzoB5mdPPJcNSa3RCl1qkw4wTL5jpI3eZF8snZLHKEybn5ugKnaXlJcRKIsCe2VhOAPUKv56W94G7fxq0O5qw+VaIgEBkbFLuJhSevbV9G9mX8TYoHjBpV9tMYzL8Xzgayb/fjPwmk1tmylPX8eYTvVibxw7IWe8JczsFuArgF/e9Ou7gTdO/v1G4J9O/v0U4I8BUkrngRXG0QqAbwP+w6StSCld3M1xZ2RkZGRkZGRkZGwbiXGya+Q/B2b2vWb2wcl/N01+9zmM99h3p5QuaQGfBG7d9Ke3wJbZ7REP2tuBL1AH7XaE4meAf8M4ZHIJx1JKZwBSSmcm0QiADwF3T7hetwLPAm41s49P2n/CzF4IPAC8PKV07vKTmdl3At85+ckd2F2zfvu8KG4FsCa8NyuCRgSa+hAponVERDkiilVzgi+wEfAyrYnrnRea56CTv4tAUrby3EW85ef6vifqs+d0jQhVY0RFsCKF7ZS+fyResy5CFBuB5aYuVpKZQBL7SNQ6uWN0TPaxOvQ9d0t97XVTdz0S8VPRy8WA4tnKwPfKriVN3+qZTyeoJ52EXBEv1Fw5oJ5TRJSgfMwL2lyE8qQ+eWoNAzgoknsDudAo4b2IeEBL1FKKMCxmlMqTaAeoifdBlIcAYF28t4MAhWdaJBn3A30o1EUEA6Ak1KQiqldKHGBVKDBFIhSqsN1UWb+z/ZEfFRoFIkvNqh+NsUA0V2uzXXtcRYRi6z5Sej3jZGsAzOw24LeBb0wpfXzToe8DnjDJkTgFvAT4hit0+Z5J21uAlzqnfgHjvbeLXYtQmNlXMqYpvT/4J29gbFXdy9gQeS8wZPwFuAV4T0rpmcCfA6+9UgcppXtSSs8eh4t2NfiSkZGRkZGRkZGR4eOSbGzkv6vDvwMOAb8wiVrcC5BSGgIvB97JOOXgN1NKH7nC378C+F4zex9wedLx4yZ9fgj4KeA71GB2M0LxfOCfmNmXAw1gzszeApwzsxsn0YkbgfPw9zfglZf+2MzeC3wCWGRsgP7OpOl/MOaKCRRuso/ifKeAZ1c9+yOCRw1wx5TvtY94QxU2htq4UhKVATous8JFGLmS9R2oq9AUszoixXuw4nuIGoE3Z77me2dm6n77Qld7jy8K/nIRyH1R8pILKssdmKv6TzeSxK5qsqwFXL8HhSZ+JOqjcigiFd8HIpKmkukBNpJ/kIo+gJY4jWA65vp3oeRrI99RNYyFwFxviKTscmf74hML4l0AmBVR46mKnqdLfX8ROhOoYH6o6UdiZ6b1HLul5SeyL9R1let+4b+3HVEZOoIZ0+Moie9+QKmZ2eSneBYBmeWe+dHHmbTgth9NOrqwih/lODn4gOxjJBKqK2X9DesN/fyHSIRiT2AX6tqllL6DLTb6KaV3AO8Qf/8g8LxNv3r15PfHAf3CXIZdMyhSSj8E/BDAhKr0Aymlf2Fm/4mxlu2rJ///n5NjpgBLKbXM7EXA8JJmrpn9LmOFpz8BvpjLpK+2gqcKsiwicQuBokAzYtFXSbmgNydTAbrSUGzEBgEdcJVjHFnOS8JkiNCV1MZzOrBpUJuTCCVhTmyiW5oJwIqg15TFs58N0A1ua/qL7UNtfcMim30FtdlrBBKdG8rKD0CJsETqmHSEas3JTkCCRyCWuOsftGg6+bMrkjsPFFLfAsVWU1QkAOqiyGPghtwg9iZqPQZNQ41sXfriNJGkfjXWyN6jKyhPETW7ZsP/EDZn9Rp0pOFvfm+e0vuSgUgOHxa6j/bI/1YqFSiADfwNcj9gxM8VIlE5QEdSUDVXIvN4XhSbvKX2TNnHUjrhtq/2HpZ9lEQNmuFIUzuve6RE2p06FNcVrkUdilcDv2lm3w48DPwfk98fBd5pZgVjztc3bvqbVwFvNrOfAS4A3/oZHG9GRkZGRkZGRkbGo8MuRCiuN3xGDIpJPYl3Tf69yDjKcPkxx+HKgucppYcIZJhf9lcUTqVHpY09FYguHKyJRDJRZwA0NWKprz3MyvBdFrQYgOXe9iVMT3f86bQQkMidl9QZ7Q1dE46oiPdmJDIaDwQKPMwJytPc1PY9Lyui1kXkfqkrORB4bodFTZYI7e6IEN8fFnq5Or7hP/zlgAym8si3BC0PdKJqJGF2YP61JFUSHmiJWkRTpsUF1EoYqfqtIliR4NS08Op3RaQWYLnvH7McoNZURNKtErgAWB5s30utkrIj4hN9QZvqd/Qcaw/9PiLPVtVUGQS8u6MdyHo9WvajCyW0zLKqdRKZHwrnu0J8YqTTlNX6oqRpAUo7kKvaqPj0raIckMfun9z2OHYVCdJOUAGuc+zjStllyuWt+cPqg642+gBDcUykj4s9/xFEpqAKfUeK0ilENO+VpnlkE6WLNek+dgKqKFTkm6AoYEOxyV4TxgLoolIR+kVZcMDOdvVNP9H2x3q4rsch6rjRDti8QzGBInOwITauqvYHQEe8k+uBal+Kax0pXqXIimfsftlDa3DEbZ8KvJTKGIgYvuqItUCxwJaoy6IcCaDnkKJEgS5aqYwFgDNiz9gO1Mo5s+4blLM9rYp2XORQRFSeFoRy1oG6dqxtiCJ8EaOktgMfmAVBAYyMQznFFmr+vmFq5BtGAEtCRW4DXduhn/wcnJqzB7sElYehciz2DHKEIiMjIyMjIyMjIyPj0WInZGOvd+xjg8Lcku2qimgkkKeSN3sBL9NOKMo0hMe0F6BeKc9cP2n3sFJgirxPU6LuhqKSgK5nUAokdqvoU6SSeiF8qn0xfyKUOUUlagfm4LSgrEQ88srzG4mSLQoJlYuBkru1kn8/IpEl5S2PJPWr9ynSxwFBr1hEe48VLaqXfKUXgOW+7y4929WRtIaoVRFwpktqVYSKpqidEe+xSvy/EGAyDoQXux24lhURClkRzw3gvnXfg6zUqAAu9PxnuxNMj8j8UJXUVT0VgFnBd1RrZeSY9YCgh4pyrfW3H2mrm//cbk43yj5GJf9izhUfk32oCERdVOMG6ARU864pEjlCsbfhy8YeEhSMuUBhOxW2jmwa1DER2VilXHLOj0qGMBXYhSt10Ug0WRlYC7VIrsf2aWSFMCmP1PXqcGhme+V21lf066mkViObrDNifkQ24WofpjjSACPRiVI9ArhFyIA9IfBM1BxcH+owvrpnlYAU4vmOfy01fKoJaB501XQf3UJtwmUXqPqLIUlpQWlaCsgaLfZEIbeKfudEqg8Bu3dHlKLUO5cCd7Uv1o+IfLqis0Xyp9RZInsxdU/V+gJ6o74TzoRuYC28IAqrqkJ/ESWpuZLvkOglPZE3bNFtL5t2ejSrvtJctXTV6qXXHRI5QpGRkZGRkZGRkZGR8WiRIxR7G2ZlKo5iw13TfkLS7dN+SXmAVZE0uyKSxAAGQmWjF1AuUd6seqDA0frQ99w1y9ufKipRFeCCUKSKKLm0ReQoEvWZFpcboV41G4HYtnsOvQKpazkYUGjS4XXZhfTaRtZSNdK1oR5IVUTSGmUd4aqLYxaquo914ZVdCXh+laezHFi+O6y67TPoAlhVEU1pBTzy6lqUZxhgTtCEIjLvDaHQtBMltAJ1ICWNsBPwYm8MFJ1Nz1Ml6BGJLqgIeaQoqrra5UD0ST3/1lDfDzVPjzb0N10JeoREHYb+3uJ+zsg+FNrp8sLIj8RGyV87ANpDP0Kx3tXqS9WKUJrbJ7tUEejdF9gnjyojIyMjIyMjIyPjOkOOUOxtpDRkMFzasr0qvPrNQA6FSt4ciuRggBURoWgFPERKLnFjEEnsFnkHAe9fhF+qoJ5LJA9DyrUGrkU5CJUHGmBx1eenyyAX4gAAIABJREFUJ1mDRL+eG8LDuBoIkix2VbKrXgmnVEZkAEo3X81R0N7yaiDqMyPqyxys6bVhbeB7GOdEvRWAeSENORrocZST71GdS74GPMDN0/61RN5JJQkcqZLeFMeoKBlAWcyhViAhZCfWOTXXzwfqP6wM/UzUDdP5Qifavnf4tmn9XqvIwKlAKtmauO+dwBqkEuq7hX5fVpI/2G5b5xwprKKFEBZL59z2TuHXlxkmnaXcLvmiDyt9XeV6JyRdOz0/2tLqHN/2Oa4H5ByKPQyzMlWnYIrarN0UKIBVEZuTiukZpJK/pwPx4hsa/kI6XdFh2pYoThQp+LQTJSIW+4peoTdiyn66bUp/rJtCbeqhtp4fy52GPMZDZOOiKE9TgfmjlE0ON/S1KmWTSHL4ha7/vsxV9ThU8nctQnkS72Q9YJQohS+1wQb9/A+Ojso+Ruaf6CBaQeWgKOIYmafLQsEr8q1dEy92J7A2qKRspUYVQSTBXNkt1cBNVUIZa4GBKDsuknCvnC9CJwEI1G0JeLRUQbmyo/p4CRvD7VPiqkI9aRigoimUxLWUAm9Uu1hx28siaRugVPKTx0slXThzVCjVmOtdwimGiFN2r2PfGhQZGRkZGRkZGRkZ1xQJCOR/7nXsY4OiRLm0tYf4SN33VM02tFVcF9SHaUGdAOiv+mHHrqhVADpxTnlLAQaF79E4FPBSHxUO+VkhLwgwLxJeI4mXZ0X1cRV9GB/jj6Ns+n6oZ6cShKcDGvBKNjZCR6mLg4YB14pK7owkmarKvqd7mjvxJcd8j3s5kEzfE9FJ5cUEOCjmcaS69IProhZKRBpSSMtOBcQWVPQp4njbCUlpNYXKItIG0Cj79K2IpKfCKODVV7LCh0RUCGBQ+De12tMe+UPCCT0TqLtwUdSYidxSta43AsIiy31ftGE5QDU6YKJyeCDavyzEI2aSlp1uJZEQLcYZEVtYtwtuezeS1N/3+yCwRj0WkGVj9zhSGtDtndqyfbYqVI0CCj2zB32jY7qnjZK1nr+iXwjQZm4TilWzVb0IXuj651F0FNAbi5mAQaEi/ReFChRAW7CzImpTRfLPEzGO7lzwPwoV0Ud/8YA8R18Uv6sFcj1uaqriirILNsQ9V88EdEi4HjDijoj6Mjcd08ollZr/XNZ6upDbulB4i+j7dw/57+TqGb0xUTSQiOKMev4RytOc2OxHNvLqkIiakBB5Yj2Qb1aI3KcbAzR7ZfsEhkFPGBQX+pqyMi9yeSLr3LowsGuB9VZMdc53Ijk2/vpQjDT9ZqEqcp9UQRV07YWlgVara+C/2+tsnR8aRUUUxjRB3dopeAWIAUoB6lURyI+5pkhGEXgP9jr2rUGRkZGRkZGRkZGRca2RIxR7GGZV6rUbtmxX1IdSpEL1Bb+CY3+gLfymiJQcCxAKKmV/ptZKOnR5uO57AVRYG2BOhMefPK8VIZRC08bQ184GOCkSgM929XNRXtmFakAtaNaPUFXr/nM53NYlzhVVYCkQ0VG1TtoBz4ryUs8E6CjT4qYX6MiAqlPS3tB9yMiR8AwDLNR9L2Rf1EoBuEHQDG+fDSSZCld3JGk/kkCuoGrlKLokwG1TvhdS0RQB1sWa/OFV/UnUdQb0mn24piiVuo8lQWmaEUnbAA0x1tkA7bJR8udypHK4yqePUMDUc+kHouxdwVd7sKUjAxdLvmrRtGlltXX8+g5qW9A3/e2YTn4EfFTSLI1m7Zjb3h3o+1USkedyRUfqe31dN+xaIqFVHfcD9q1B8ZmAMhj6gfwHNcki8rUbff/D8Yl1HeqNyIsqTAnDZiDoORCgvexAUboIhUfJ1yo1KoAT5/0PR6PiP9tWoDCi2nhEKAsmaFFHheEDOpdDbeRAG0ejQALN+a4/joeXtEGqnA3rAQU4hUgukCrQGFE1mhfF4CLGgsqPWdiB4omRcag51hvp57Ik5mGMmudf71Pm9MUcEvl1SpIc4Iamf70nNvQ7tyre/YjKoNjHy4KEACZ2yGoOAhz1/Xs0K5o6s9zzn10kL+Xm0e1+H4FtV918C3u5dN5tbyT9za8n/xxmWztkL6Ff8/NSOn1f/hagP/TVpvYFEqTHQFL2ThQGzcjIyMjIyMjIyMi4AlKK/Xc1MLO7zezDZvZBM7vXzF6wqe3FZnafmd1vZj8Y7G9j8v87zKwz6fdDZvZeM3uS+vt9G6FIqU+3d3rL9mWRWLmwLtwdaA9yxCM/ElZrxFOlvNR3TGt1nOWB79E4GYgonuj4HrEjdU03UVSRaiBC0RSOuQhdSalNfWI9kOguEurvnF9z2yN1TJRe/XwgwqWWgQj94qbprtt+LFB17Ejdv1/3r+vl6qKgNZzrai/lnHj2q4EIhbpnRxr+/QK4pemvH7dM6+zfnvDsqmJgACPxlYuo+Kio4bFAFKwhIqCHajrZ9UZRbLQ11Ou+ws1N/WwPiWMi0ckVMQ8bgWKTETqSwryIgkaS5dU0bAUiWOfFbY8UPtwY+CfaKGmlqJKYY1X0s60n/1t5qPCpRi3TH+yR+Q8/BWpZLLUf8M8xur6pSJ9J7BLl6Y+Bt6eUkpl9DvCbwJNtnFH/euBFwEngfWb29pTSR6+i7wdSSk8HMLPvAn4Y+GbvD/atQZGRkZGRkZGRkZFxLZESu6LylFLabOFO86nsmucA96eUPglgZr8O3A08wqAwszuBtzK2Bf7AOdUc4JdnZx8bFGZVatWtrfgHW76nUnnDQHN6IxEKdZZIVd62yNVYEVXBAc53FV97+zx6xQkHmBV93NyMJCr7XsbVAJ+/K8YaSVQ+2fG9TFOVgL6kgPKEDwNekXXBo47wly+I2h+VQJSjJc4T4dmr5O+ZSJKpSO5tj3SUoyakNHtt/exPtP35sxgoILsmkhdU9AFgJJKOIlH6QyI4GUgHYTqQdK2g1qiIF1tVj+4Ecud6Yn5EopPKqx8RQlD5D0qWGmAg1phItW2VkxaRFVYSyKqeCkB/RsjG9m6SfaiSGa3ADVkdiWibyjVEqxyoCESvpJkNC1N3uu1DEUkBaPX8WhaDgUhQB4p0ncvGYruWlG1mXw38B+Ao8BWTX98MnNh02EnguVf489cBv5hSepOZfe9lbY8zsw8Cs8DUFn//COxfg4IS1fLWH22lShOhGqnCZd3AYjwnEnOV5jnoj+TKQI+jFfmiC5wTe/0nzOhxKAUdda0RRCg8qt7FYk/3cYcoE3Ci7Rs+kWtVn6YIHeWQKNB4WNDQQL8LS0I4AKAvrveWaX0/lsVQI0a+SsyNGJOj5C+tyogD+NtlRTXSG5OGqBjXD4gx9MQkuqGp74dK3I7cj4rQq6+W9OdM1E4MYX3gX+9ywIFzquMXNF0OrNlqHB9f1c6Xw4JmGJnr2iEhu5DG0cmNgLiETA4PFMcTSdmKEgXQLvyXai1AR5oTxe/KO1AwbigoT4OkDYoi+ddaEu8s4O7TAAZDXTso5NW4xijie5fDZnbvpp/vSSnds9XBKaXfAX7HzL4A+AngS+CKhY6udJeeD3zN5N9vBl6zqW0z5enrgHuAF3sD37cGRUZGRkZGRkZGRsY1xdUlXF9MKT37Sg2TKMLLJj9+eUrp7xOFU0p/amaPM7PDjCMSt27601uArZKKIyN7O/Ar6qDHrEGhbMWIrGPE062gohgRuU0lhdgLeOWUXr3S5wY4LGK9x9sB6pWgzkQ03hUWRNItwAGhE98aas/LnSJRuSrobA+3dNhazZ/I/Trb9a9lMeBxPSju13SAaqQiMme7ehxKWvZgXfOE1HOZ7WpxARVtiXhtlbxxJLqwIt7bfuC9Pjblz49bm7qPgyIKFgmQquTeSERYHbMmvP6gv76LgdovCs2yviH3r4k1O0ADUaVMAqwpVvoiYhOI5g5k4r/uY30g5lih148Ddf/ZzdX0sx0W/k1dC1QwPz706zd0zI8ezBVaHvsAfpRMJW0D9ESSej+QlK3oSjPN22Qfa62PyGOuJXaqDkVK6fWMk60BMLPHM44kJDN7JlADFoEV4AmTHIlTwEuAb7hCl++ZtL0FeKlz6hcAfgY++9igSBT0h1tP9jVR/CxC0VgRG/kI91xt+CIR+kVRdO5iVy/GZ9r+7qQmiheB3gC1xT0HeOqcv+G7IZBDsdL3N3wrAQUVpY4TebZKDUjd0QjtTuGUUN6KjEOb33C8tf1NlDrLRmDXqfbHZ4TyVgRrATqKol+0Au9CW/BzLvS1cdRNPgesCDinbhz69VQs4FhRj24pYLR2xDsXYLRICmA7MMdaYp9VDayVat2P5B2o+VG1QAFP8ewiz1bRh1VOAUCr759naaBplwrqnYwcE/FnqVyOZkB96+bCL+Z2SsyP8+VT8hzd5KsMjgSdCbTBsNE7K/toVnXhuv2AXcqh+Brgm8xsAHSAr0vjQjlDM3s58E6gDLwhpXQlq+sVwFvN7BXA2y5ru5RDYUAf+A41mH1rUGRkZGRkZGRkZGRcUyRjFBCluepuU3oNj8x72Nz2DuAd4u8fBJ636Vevnvz+OHDVGtr71qBIKVE43rkTIhJXiKRK0F7GCG1KqYpEkmqVAkYrkIk4SD4H49ToouzjwpKfSHZn0w+xAhxr+NGDCM1MUVYiyc4n2v6DWRMUMdAKKeqxRFSxlDLSRS2JL9VgjtT1/FFMgEgFYkUTiijwLAsP8wMtTVdSs0N5qEFH69YD80clgEaiCw3zr1e996C99q1AQrWi8Byt65s6JWhzkWTo+0T9mBMb+n4o+k3Z9DjmxDvXC3w8zvb8l3sdTTfpFv6eoRxYg9T8WAlQnnYCy6y77YOeVlZrDf33ZWmkE5UXS75qUaS+g0JZJDuXAknbvcKnK6mEa4BB4TMGhoH7NarMuu21slA32QMYU56u9Sh2H/vWoIAhQ6ek+5oIsS4E4ud6c6s3rooXrDiuO4WO4jGiX+onTPsGw1SgwtHpjn9Ma6j5p0cb/oJdjxTHE29GxNeg5kdNyBhGck4U9SpCWTjZ8u/X363oTdbj5vyJerCux5HEBlkVrgJYETKpEQllJS8ZMdIU1DgBlkf+iSqBWbiBT4sqBdaoabH5XQywUVoj/74/ZVbTt2aq/gYn4ihIoqhYTahiAawLPlLECaRZL3ocR2piLQw8FzXWiANnoeaPVa0vAH0xkKrpuV4vfGPgrmn9DXv8rJI+19+fi12fIhiRwH247W/ElVJUKfmbdIBZ86lGrZJWV+qWfaOkFFmjemfc9g6+gbZXEFHs3OvYxwZFRkZGRkZGRkZGxrXFbtWhuJ6wjw2KMuXy1h5zRSdQ9AsA4ZSlGqAkzFVFpCSgSKSS71SNgDF8781iT4c/54WnKoI7pn1vllJOAn29921o2sspEamNhPFPdvwJohIvIx55VSQpktx5qKGoRnqZeGjDj3Ddt6oHMlX2n1uE4rMmkjcHos4J6KiP8lCDpsWc6Go6ykOlj7vtFdPe0mHyPf8H042yj97IV4xZFqIQAHXh+f+Tjr6Wuap/TCegnNUSy1g5kLl7tOm/160Ane3ExvaTjBVdLVKnRBVHVAU+QYttHA5wFU+KB3Mq4KVeFVSjY72nyT6KWX+tmwqob6kg1yBAZzMxDwtBm2qK4q7jkwjBhkBxxc7IL55cLun3uiQogtd/0TqNRI5Q7HEUJIff9/DIl2WrbRySZzja9BfKmQDFZ1o8gRQIfSvJziUh6wdQFcoUarMHcL6zfW5oU5wnBSqAKqGWM5rWKWU9z3c1RePja/5YFc++E1Kc8e/5MPDxurHkb5BumI1Uqd2+UXtGCHg9vKGN2rKgRkQohMpe6BcB40hwWiIKPMpgqCb9sVbLRzmQK7YTn0FFeYvIpA6FkydiUJwXL3ZERlep9Cj6DmiK6Vk7L/soibke2RBe7PqOpHaEpiqMgcj7cjZtTU8GqKPn+rwdcdtbI71+fGzFv6cR2q4ySpVxDdoYVHSkSJ5GTawfpbT9JOL17lalDz6FiihspwwOgI2hzvG8pkg5QpGRkZGRkZGRkZGR8ahhOyIDf71jHxsUyVUpaArrfFa5j4Gm8DTM1wIJbYLSVBOKRQCroh5GJElwqaeKAulODjdE6FIPg2WRLB9Jh64Lb2cz4GVaE27qUoAacYOIOqsFRhUbBB1ZUoWaAC50/Ws9vq6f3BPm/WevqH2g6wisBzyMs2U/BKFoigAlMVPPBHTklTZ/M+B1m0l+cmcEfXTdlu0iUjhTUWsi0VyF9UChv4Hwlqv3CWBBSJqd72iKRl8o6BxMWpt/QyTmdkQ7QE98HNQ3DqAhCk2sDHU0d6ns1yuYDrwLc4UvCnLnrKYBPe+w/z2+a0bfU8UqOB8ojHlWRI7+eumJbrv6fkVwc6A43oMi+bs6o5W1VL2LvlCjAtjY/WVuW3isUJ52Xhh3AjO71cz+t5l9zMw+MimcgZkdNLM/MrNPTP5/4LK/u83MNszsBzb97uvN7G/M7MNm9geT0uIZGRkZGRkZGRkZ1zVSstB/exm7GaEYAt+fUvqAmc0C7zezPwK+BfjjlNKrzewHgR8EXrXp734a+P1LP5hZBXgd8JSU0kUz+4/Ay4Ef809vmOMFvLXuW9YH69rWUrUIDgYozvMiQjEjtNdBe7rrgcqtKolUeaEADovk3gg6wmMWifpMiwhFO8C1Vkn5hvYy3TYVOJGDYaFfz1UR0QkE2qgLr+wFlVACfGDR98pGcnDWh76nKiJxqqoUT5W15045ZSPvggouRfqYGvheSpWYCVASvhcVqQVYqPs35JB+FeT9WNJObHm1kdyF1sifpwer+mJmZJQrIE089L8/F7o6absjJIG7aM9uQ0z2A+LZAxxr+nP59tGM7GN2+bPc9vvRlZ+Plz7qtp9q6QjFjVPPcNvrZd3H2sC/Hxd7gUR3IQxRFtLn6rkCmFhPUyQBXchBbwx0peySqKkRSezeC4jUJdvr2DWDIqV0Bjgz+fe6mX0MuBm4G3jh5LA3Au9iYlCY2T8FPgmPqMhjk/+mzWwRmAPuj41i60+QUozpB56+ogGt9vXCcVooAd0+pcdxrOF/fCJKHUdFQbnIAqUoOgGmCBVBJYpoeCs9+sgmW0WMI3r1kXoXHqZEPQTQ1KsIbWpOqHO94JjeZCmbI7KYdsTH6b4VzWnpDJVAgb4WVYBosacNLJWYuTTQO+imMFqP1LRAQVckGa+P9MZVFSWM0GIOCkfA587rcUxX/IGsDDSf7VzXv2cPbOhrUYm5SqkOYFa824t9/WwfWPePuX9d1yJQDK/I+tFShe36+n1RBvZTuVX28XDfp+hMBVTR7l/zn11E8W6h6vcxE6B/rgvlrJFYUG+d1g4c9ezPBURWlJNnoXq77KNT+EpREcfJ9Y70GEnK3jXK02aY2R3AM4C/BI5NjI1LRsfRyTHTjA2LH9/8tymlAfDdwN8Ap4GnAP9ti/N8p5nda2b3EpCYzMjIyMjIyMjIyNhNFFjov72MXU/KNrMZ4G3Av0oprTn6yj8O/HRKaWPzMWZWZWxQPINx9OLngB8C/v3lHaSU7gHumfxdSo70mkpWvVnnEiEKyHIhEMYfCKu1HYgu1AWN45YpPZBnHfK9XR9fk11ICthdogopQE149SMJ5srDrChRAHMijKGoWQAHa75HXVHVBgHKk/IyBZg1spLtjJrowG2iCO0hIW0MsCLEBR7e0Bez3Pc93YGcW0TObYiupJz2CxXtLV0V0YNIlGxV1NtRevegpXargUicohkuBSqYV4VARU/QRABa4phI9HIn1qjV4fZ9eYqONBDedtDU3kiF+0VRh2Q5ULPn+MCXQb2jppOyn9D0j5kNrGNPnPPH+uyD+kN4ywH/mFLgfVlt+d/jh9b86NO5QOL3yY7/7CP1VKZEvYtpUY0bYFTyv5PT6D7O8x55zLVEwhgFapvtdeyqQTExBt4G/GpK6bcnvz5nZjemlM6Y2Y3AJcHt5wJfO8mRWAAKM+syjmqQUnpg0udvMs67UGfHHJ3uA4LmMbsDuQsLAb7/fMVf9CO0mYfbQrEqcC0KZwMi70oZS9EeAP5/9t48yLOrvBI897fvW+5rVdaqKpWQQEIgA4YeBqwmmqBtxgbbMc04bOOYgBmmJ8LRbiI87Z7xHyKY7mhiTNOtYMDgHpruHsZtBdaAGWgZJLTvpVqzsrJyz/xl5m/flzt/ZFZTUld+5ytlpXLRPYoKVeV7ed97991337vnO9/5egKyrEEj30qRNsIKHb3HyBP6ApmMASDuV9jOCMgE+Een18h92pfgjjPsY+5FOSINAHg6K4+PsOIjnH24aoqOsToUFSIlAIAWeeY0hanqZFWrKdJXJUXp5mu8jbwpidtTxKUF4FrrkTCfG9jd13xgl8ry86AYHpRMaCjcpvqD8vyRViyeq+R6NSIPWnPFyz8qB8Nyf/QqrgUgBSlJsTgACFblj8aZujyOASDrkWt3dJoK963uHeL2kJfng3RI/Qavoj4IQ4i8wzLkHbgB+b5U2lw2VWnLz+S0lReKAFBqybUqct1p2sZ+wH6PPmiwYwsKs0F9/Z8Azltr//kNmx4B8BkAD23+/68AwFr7gRt+908AlK21f2aMGQZw2hjTZ63NAvgIgPM7dd4ODg4ODg4ODg4OtwtMOXEQsJMRivcB+G8BvGqMeWnzZ1/ExkLi3xtjfhfADIBflxqx1i4YY/4pgJ8aY1oArmHDKWpbCBGmShEdpRWoFeY46CGsvaYORS9hI3JESgIoXCUU9N9QhLGM/FqYh3eERHQAwE9Y+5oiysGuViOdqbRlyt0Qlpol9wFAnYRRWY0SgEfB3tvDZ8Iy6dNrFd5hLNc5qtGjQO7zSwXO3AWIU1RBwXQWurIxelvxLMRIlCyqSBDNvAUO25oo6smEzDD3J7i/fyxRF7d7FcmuxXW5T19akqstA0CJPFODIfk8AWAkJfdHWxGxmczJEp+lNHckYtHrqCK6zaKPb1VBryDI9So+6F4pr4vbl2o8olcalKMYGcW8zt77TCrN3oG3CwFy7zOtIdpGzSeHwIsN7vC11/F2qUOxky5Pj2Pr77IPk9/9kzf8+18B+Fe3eAaQcihYZFvz4RolH+F1haaXfdz6FC/riWRe3N5o89v8ZFYOOfeE+AuuJyD3GZMzAVzCo3k5DUaq4vZ2l18LkwFVFdIZpmNlYWvNy9xLxo8mB4eYtGBckYMTIed6Kq6wWiX35WKZO9+czcn35ViCn0eSfJheKnIpyQt5uc9yRJ4BAL1GdkiZYBoxcFKj2OTzXA/R0dcU81yWuCsNkg9sAAim5HM1fO2MCMmxGY7wClkrNT4OGUJBWQ4ZSPK5coI8L2eL/DyZNKY3qHEBk89jzsPfP2sN+Tg9Pp7UeDwoF7Zj9rYAcCIu98exmPxuAYCR1Kq4nd17AGiRRevVNXkxeanE+2uF2NcuVvnccKEtf+x3DB/HjbYiQfMAgJGlBwEHuFK2g4ODg4ODg4ODwy7CujoUBxoNsvjWsG4sAqGJUDAnqK7lLFODsNCa5GAPiQwEFBofJpvSSCNGojIDpNEhpqKy5CAc4v3BIiWLNe48kW3ILNO7M/K1DsV5YapyQ06KO5uTWTsAyJJozN9mOdvFmD1NkiBLuNdICEeichsatylW/C7s45GBmIdEMbqDtI08ZLZ8oaKRMsrXqyk4mCQSjQnyvAFAoSWPsbMKqVFvXj5OqcUjR8wpqtDk95a56vWEeX+sF+VnKrfM5/0SqbuxyIMtuCclj4/eMG+EJRnP1/kcdDgmX+/VsiZyxF4O/N6miMVb2s+NMkJluU/7DJf3MaRD8ofDUZIYvgG5z5txPjdcqcn3dt5zlbbhJfVBQj5FcjjdY3dhYWiy/kGA6gqNMR8w5vUBZWPMu3bmlBwcHBwcHBwcHBwOBrpW92c/Qxuh+CGAZ40xv2GtXd782dcB7NtFRY5IQ5N+virOk6Ts1TrXIL6DEN0ZBaN6viSv8H2KCqH5lnwtk0VFJduMzAAxrT4A9CdkVj4U5tGFNtGf+oOcLfcRFjKhSABlif9rJLrgVUR0Ql75Wo7Euea3l7CyES8fP7mm3OdL9e0/TxqwWijpAOdQWHRS46vvJ5aeGR9noNvk7TIUUSTck8TtrGKOYgmemgjo3YeWxe2xUYXWelW+Ly9f5lGfekfuM42JQT+ZGyIhPlca0qczpM4AAEwTu3BNlWsWOUorqo8zpBVJyA1i6FHv8OflmbrMhlcrA7QNr5EjR17Do2DsarOKHByWK8iiZBrjEZZHGlbUa0p65ET4HOTq5QAQ8cr79HZ59PIxPEf32W3sZA6FMebdAJ4C8Clr7f+9+bMHAXwFG77OX7fWPqRop2ytjW0Woz4P4CI2cqErAH7HWntR+n3tguIigC8DeMwY87vW2p+DG+HsaUwW5ZAhC8NtQH7g+hVJYCzxNuXnL1pWWGqqwl8KLTILaqRGTBU1HOFSgMyYHNoODPMh2y3JL/TZl7iXeLEhvzg0xasYGsShab7KXVqYG0hMkdg9TqRVfQrXmoWq/CLWJIdXSLHJKYXEh43TsTD/2GN9Vmnz+3KuJPdZB/y+HAnLcoJeRW4wmxtU0k4yNzS7/L4EYvI85hvmF+Mfl8fQe0aWaBuNRXn71NUMbWOlJt//jmKs947Iz9y9YXKiADpXh8XtSxHep3M1+d0QVxRgZPN+RdEfbDodj/E2At4j4vZeUggQAIbD8mA/pDCoOJqUk4wDPv5Oz5ExViNGKzHFIr9Jkvony/y5jvrk8/AqDGE6kPujfBskYruNDZennWl7Uz30JWwQ/zf+7KvYKLMwh42AwCPW2nO30PQVa+09m+39ATZcWj8j/YJ2QWGttd83xlwE8O+MMd+AyoTNwcHBwcHBwcHB4e2LHbSN/R+wUUD63Tf87H4Ak9baKQAwxnwXwCcAvG5BYYyZAPAdbKwFfiAcIwGAlrjVLigMAFhrLxtjPgDgmwDeofzdPQm2sg55FRVyZBofAAAgAElEQVR1yZJTsyJlicx1hcVpT0BmXVm9AwCYgszIxxQSMEWXUVw53yNuT89yCU+yX2Y8gooE4XxT7g9WgwQABkPycRizpxk/Ea/MdJeIpAEAEkTWkFYkZiZJIqrfzxn5ekM+j8QaT4S/VGKRJX7fyqRC7AoP2MAS4YMmWTFYOyFuTwaitI3GbQilBUiUY7HGWezyq2Pi9okZbh05NC5X3e22+Fy5vChLiWYrvE9rRDY1r5Ar1chzGSDPNcCNI6I+RUV3chhNvR32fmHRbwA4lyOJzGH+/ukhEYiBED+RYSKpZdFcAOjvJxGKhKK2VEs+TmlVjj6dX+b1Z5gJhqa/2CdktCo/9wBwuSo/1y3Doy37AbcwE/caY27UcD1srX34ZjsaY0YA/CqA/wqvX1CMAJi94d9zAN5zkya+AuBr1tpvG2M+94ZtRzdryMUBRLb4/ddBtaCw1r7zhr9XAPyGMWZc87u7BWP8CPi31kwy/XEf8V4HgDL5LmV6boB/4CzVuVxpgYStU4qPudsRbmKvcxamBYAOkQEtKCbKe/yyXjugyEthL2uNHpK5BbFjaLTpwyTnJF9VaI+Jp3nLch3snQl50dFPaoMAQIcsnpl8BwB8ZBCyMD/AF3LrihyKjFeWgEW7p2gbJcgrl4KihkSFfM31hPiH2pmkXCPi5JEsbaPdlPt9dlEegwBwZVJ+9q+W+WKA1ZfJKxYlhyLyc5lWSAQLdeLOVuCyTPbumObfvrgjwWS7nEwIk3mqopj3K22ZCLhY4HP2UlW+lvN5hctgRD6PVwsy4QUA42Q+PRrjfXq4RyaDu2Qe05CITHKrIV8aZLIst/h9W/PI88dql5Mvex3WAm19hGLVWnufct9/AeAfWWs75vXFh292sJvdrPcB+OTm3/8CG9Kp67hR8vQpAA8DeFA6GfFJN8b8H1ucxHX8j9LvOzg4ODg4ODg4OLydYW+D5GkzivD7m//8GID7AHx3czHRC+Bjxpg2NiISN4aHRgEsbHVqikM/gg1lkghGHdwYdvmnAP6J4sB7Ah7jQzS4tTtAmpg1xBSVskukQqjGNz9KWGzNeZwryhGK+Rpn3UokmlJr8/NoE5/lqI8z7mGShF5UuI7MZGWGaDDJqbtMUE6+S/gVSaQkYZqBVY4GgGxZZsJZfwLAGdIf8yRBEADmiOMMqxoOAL2kgqzG45rNjKvEjQrgid1MzgQAAa98tmw7AAyShNgzaf6CChHNymxVkSzflp+58Bg/D++YHD1I5rjkKfu0fK4aRrU3KL/yXshtPzKQUJhPxMPy/DKnMGR4tSA/U5qIHnPySSsqQycy8vVqJKYRn5wMnwrw/sgRGeqLazyh+goxU2gp6kKNk7I9zJkPANZL8vMyXyHzvkIy10vuy2yVz9lMzuZTaOaSLfneB4mTFACs4Am6z27Cgrt/qdqx9qvYSLa+jonrfzHG/DmA71tr/6Mxxgfg+GaOxDyATwP4rZs0+cTmtn8D4LeFQ78fwBV2fuLsaq391g0n+z/d+O+9Dmu7aLa3dgfIBOSJtFdhLdrsso9b/jAVyaIkqZAr9QXlofoKTaUB1hry9XYUNk9s7kiSYjwAMHxI1lMeDa/TNmqr8kfjzALX4hdJkSxNvgjrDx8pCMUsLgGgROQEh/188aQpoMfAck4iCrcphhLJbQCAErE/Zi4uAH9q/YqX5FpDXhzFSQ4XAKSJJjyuIBvYONU810xrXbzMFyXJkPxh6okrFpz3yrliqTUuvaoty+fKCoYBwDyRVlUVi+eejOxcc9/AKm3Da2T5TZbkJAHcOnQ+z4vSFYmsclqRU7JMzpXJQwH+3H5wkN+XI1F5jB2K8pfpcK+8ONbYlleIFfwCWVCcI4UTAf5+0hTmnSvL81y9y+d9liPRvS2f4ruPt7LGhLW2bYz5PDacn7wAvmGtfe0mu34BwHeMMV/ARmL3jbieQ2EANAH8HjvurVTKdq5ODg4ODg4ODg4ODmqYHa1DAQDW2v/uDf9+FMCj5HeuAnjghh89tPnzaQA8NPQG3MqCYl+haxso16a23M6KjoUUcpUIaaPJ6B8ADXIYjcvGqYQcpu0LcqaKhc8vF7hcKU8s/qcKnO2KLMuNJHu5nMBP3CkiAX4t14jbS4WTTNvGGik4BwBxwvyvKYooZUjxu8PBPG2jUJGPo5Erlcn1zhBZFcCNEMYjnBdhyfQDYX5f6kQmlG1yJrxTltvoI/IdDTRF+lYJezy9yCN+IGUVMhGeqNozII/1RpXfl/Wc/FyvKuR9jPmvrPP+GKnLz0uCSC4BXi9lRiFZYXn900RSCQCtrtyn16o8sjhZlMfhaJTPIBlipNKnMOPoI/3en+LR3Gif/A4L9PNriUE+j9jUvLz9Ki/ix9zZGlSBAVwhSsUVKysOAGDFTIvbPaq3x97GTtah2EtgSdkl/CIyETHGXB8+Bhu1KfgXooODg4ODg4ODg8PbFJocr/0OlkPBxY97FgYes/UKm91aj0KzyXSd1e3LxrFQ4ywks4i7HStjr+EPA0tCP1vkbPm16oi4PTPPO/VUSmZFKorEbmbFW1RYY9dohVh5++EoT4hkWCb2lABwYVnWYocUCX4DMVkTHg7xDquTHIl8izOdrMdzCltQZu/HDAwAYI1EIIKGX0ub5DdMlhTWkKQOhSKFAoeixBI4wSvZNsm9W1ZYvr6UlcfptIKRZ3e/pIg8DpEIaK/ieblCkm4L6/zVy2oYvbzOo+wnk3KPZAJ83g+SSH1MEUirtuU++976JdpGlNhb94NbE59Jy/1+mtw3ABhYlCMUR0glbQBIp+S5v0XMJdrEEhYAlhvEQpkoDgBgOCq3Mc0DFEigX9zewf6vQ2Gti1DsaxjjRyCwtcsTc8AIKCRPbCLVJDUxSVO2wdt4fk3++M2Q5E4AWGuQ8HmTT4K9ITnUH1K4jrCH7nyRD9moV3ZqSZFCgIBCzqa4t6zmAZPVaRa1iaB8LREf/0K6SJImNczKZfKiTSmcXpiEw6/ojwDJQvarCnXJ8Csi8FUr35esWaFtJNuy+0kmKG8HgNGo/OGxWufz3ESPLHnrv4vLEC2RVnVe4Z26SOR7g4pkV7YoZQnoAE8m1CQQs/fLZIkvOPNN+ThrDT7P1TqyxGtMIUUbImTC0QYnNUJeeTEwkD9J26i0WX/wD1NGnPUQJ7qNfWQyYVGxeGbyYDZHVRSGHmzRoZH1MhIx5+HzXMPKMrJye4mfyD7ATudQ7AUc2AWFg4ODg4ODg4ODw27DRSj2Maxto9na2uKtSVbnGsvOApFPMAYJ4GxnikfxKa6UOFNV6cjMSz9h/TVgnucAjxwVFbKXVVINN0iSbjXnoakxwpj9OolgzFZ5QuTdYZkd7h+QqxwDQJDUqjirSDJlvufDioq7XtLnraLCj7xGKv+GOEtUI9GntbpCamTkZ65peH+kjcxkahJVYz5SX0YRaSuR5M3kIo9QeMmt6+vj4/QYsUguEutiAIg15H2uVngbC6SuT0+Az1HMTGFCoRM6X5Dvnc/w8VEnkjgNQoS179yG6vS9XC0L1OX+GI/xSMl7M/Jzed8EcRcAEIjI97a4ppChrshV4Vndn3WFtJPtEVGYylwry+8Ov+XX2iYJ6O2uQnu1x3G76lDsdRzYBQXQRbe79eTQug1l57tknyoJwQJcjjRI9LoAECJFsn6miBgaEurNdfhHw4RHll71KyQJp3vkOhMBRV2OLJHfPLcmh9cB4EpZ7o+w4skpkxoj7CWqedUXSI5E2vI8jMMnZUnLcInL3Uo5/uJgWCnKi1bmSAMAE/Hth5XJO5LqvQEgCflaapbrudchf2RX2vwri81Ry1X+TOaI1Mg/z2/MCvHNj/q5lITWdVHIVNkeGr0/ky5ocjmOx+SPqMOkHgIAdMjH2mJ1+5LbSYXLU5Us9PIt3qlXK9t/bhMk3+Pdaf4Ou/ewvGBIvUvxod4nS0ijpOYTAPRdk12ccpfkd+2zs4P0GHlCvKUU+tCQR14891aP0zbmKvJYL/m43O0nuFmJhb2F21Epe6/jAC8oHBwcHBwcHBwcHHYPFoCCX973OMALCi+83q0Tm5hDRkPhksCixXXFCGoSFiDp56zbaFhe4Ue9nD3+gUyIoGy5RCNGrqWqSHjMEzY0rgh/MrazT5FYd7FIKmUrEnPXm/JObXJrWY0SAOgLylqSTFEhrblLPlDoAZ78m/DLTJVd505A8SfXxO1ZRU0NBk21bTZOCwrGNd+Qj+OvcZ/4VciRoboiaZK5PFUU0ZYScUXrUUhaGKt/qcgdyNeJs816UyPRkPujVyGJY1HjSpu38QKJ6EVUzkjydk1UOR2Q721MUY2dveWiRN61cRz5gp/O8mvpD8l9ejXMI0djWRK9fp7bFkV65WravtsQRY0k5XdYhtRzAoD5mtwfmm8gZnh3OypIlM323Q73At4G64mDvKCQMUO+b/wePvlkiWbTGD6RshwKjW3sSJgU6VPkLvSTYl0LVf4RvkK05VHy0gCA2ZosBdFMxRNR+VzZhwkArNTkF2m9w1+0ASIBY/fep3CLqZAP5FnFh1rwWfnLpL++StvwHyEvYkWFRku6VJP7wqSKSZIvsrGPvH2mynM5eomUcSjCF0f/KSsvBvMKDVgqIA+yhJ8/k0Wy8mV2vwCX962QBRjA896qig/5DvHJ1SROki5FXCFTXSVkw/Or/N3R6MrH8SusidkcpOmPBllQapyz2HObIgsfgEsRn1jm46PcksmTdJbnkxXJOOwL8PHBnMLiRPrLbM8BLjObr/AxeLUhy2ULHlnCDAB5uyBuL7eWaRt7HRuF7ZzkycHBwcHBwcHBwcHhTcJFKPYxjPHA5906oezlghy6LDY5s8vC0nGFYX2Y+Oavyrl7AIDpyvaYcICzO0u4TNtYqMjszmBY4fhAyJumgjJbI04urGAYALSs3B/1LmdvvEJhRYDX5SgpGFfmNDaoUAnlSOJl52WFpOVFmfnvKMLn2crWdWMAYIG4DQHAVEVmZe9KcilAkCT3MoZaA1bnBADuiMpRn7SivgxzaukqRAkBj3xve+JckpAhksm4Iin75ZzcH1dK/FpYj2nmFyZ11dQq8Hvkl8dAhEcX5oh8K0KOAfA5KBPg13KCSHw0RS3vLckT1fOkqCEAPLUmX2+/Yi58b48sXdDUBnqlQIoWErMOACiRLlupy+Mjp9DLFpryQWqWR3NbRm4j25mkbTBEfFxyy21DdhmusN3+hrUtNJpb2xutR+VJcFxVJJw5RfERNB6RH/ykwtXoNaL3fzq7fQ3iKdxL94kRHX2UWFgCQJzsU2gppDOk332KD0ID+VquybV4AAAJv3webKGnWficiMva4hFSdAoAWkSywGxDAe5gsVbnb/NLJVlKlFNo5BmYuxsA+InjmcZpc4VIvo/FeSO/3C/PDZpigUxKcrHEpZ1MsqKxBe0dk8dhr5fPUYdysnziIwrL13xZHmOvrnP3LVYcL6KolD0WlftjIMRldS/m5X2eXuHjg823GpmGj1xvYlRRSJQ4/dxJnKQAYL0pf3i+v19+5wPAifvkPC4Nel+Ux9AMKSQKAMsNmYxiUsaO5c9kljgEXirwNtYJAzjoPUXbYBbaHsW17PXSd8421sHBwcHBwcHBwcFhGzCqUgT7HW/bBcVJz6i4vS/EV8VrJKxYbHKmKkzsgtIKFnIwJN/GEUUCKDtXDVt+KiUzdymFY1WUJN4GPPy+zFblfbIKGVmZ2FeEiFQNAIZD8r1jeconYvzeH07K0r3BQ7xgGEuGnp3mrC1DT4i7tPQ2ZVau2OaJhnlyb+cVyYrpgPwsaELXa3W5U1lUCAD6Q/LzNKyItrA9NJLK0bDcylyey0MrdTl60JfhIb8wcbYxHs6E1+pEhqhI/F+vyPNtlkguAf489CsKQY6Qa2ERYwDwGvl6m4pxOrXKEpV5ZKBGxkdN4az2row81w32cmGMj2hETYTPH8fj8nlMrMmJzABQXyNFT+flPn9ujc/ZayRpXzPPxaws7zIKpUeMGODkugfE5clJnhwcHBwcHBwcHBwc3gyc5GnfwwOPZ2uNYJQI2JOcZKIsY05REZNVUz6k0OMOk6S3wzF+MbWOzLwsVvnjkCDkjYLUx0RMZiMSQc5CniTa0FcLchVjgEc5KooaIyGvfP/9JCGyrQiRekkb/l6FBvqwzDCfvJsnVbamZU14PcuZzu6MvH2xzi0bfUY+jlEkVfrJPhqiKUE0zosKG+anS7Ke+/4Yr4YbI89kvqEwKCCRkHqHM+EzJfmZe2mN39sASZbX1LlZYsmsfHpBi0yFVUUkbZoYWIxF+LyfJVa7xZbiubVyG5paBD/NyvdWU22b2aRqbIUPRUhEeEmRcP+4HPGNphTJcwRW0adekn+XJu/JIDEwAPj750iCfx7W83JEZwpkUgfg6Q6J22Nm+/WH9gJcUvY+hsf4EApsXTzKr/DFZ2CF3MYUH/IlsuZgIWkAON0jJyuORPkD+fSqPAEVFQmxK6Quhw1q5Eryy6df8fGSCso6jjFSCBAA5qrbn8RoMiuJgQbJhA8AF8mHWHKah4tTp8k4PTFM2wjcI9+XQImfx+lnronbY0/y+zaZk0P9IcUC3U8+XOtdOcwPcGlekNQoAYChrrxg0ITQ6+RyEwGFNz9po6H4kE8St6CaajEg91lLsQDPk3mM1Z8BeJ/FyccgALASIueKio854g5Q7/Cx7iHmE5o5KE6G8kqd31vGzxT42ghPr8jbjyX5R/b9pMZMYpH3aZnUZdEYQ7DPkxCZoxhRCQCsVmBNQZr1BuV3x2qdS69mvFPi9qjdvuR2L+BtsJ64LYUMHRwcHBwcHBwcHBzegI3Cdro/twJjzIeMMQVjzEubf/6XG7Y9aIy5aIyZNMb8kbK98ub/DxtjapttvmyM+bkx5iT7/R2LUBhjvgHg7wFYsdae2fxZBsC/A3AYwDSA37DW5owxHwHwEIAAgCaAP7TW/uQN7T0C4Mj1thi6toVaY+sKjIwjIPmQAHiYNksqRwPAakM+k/NFLs8hLpfwKNbGSZIw7fXwDmF92kOSXQGg0ZFbeS7H2eF7UoQdViReZoLEvlYhjWAJnjGf3B8lhVVii0RsHrs4Rtv4EGbF7bFj3ErRd1quIQFFDRJvWt4nHuMZxNklmS7V1IZh90UDFhnQWBfnm6zyPGc6EySKWlawkEmfPI41NSTYi1LT5wFSV0FBpmOVzMkVVggHwGhUPo+MYp6rk3lumWwHgByRq1nFvJ8ndWw0Y+xQRJ4MNe42BWLF6yFSRgCoksJQTKoG8HPVRNJK5Foulvi83kveP0zZsKYwW2iQCNd0lRsDJL1yhKKrGINxK8v/erpcDrnnYXV2428SP7PW/r0bf2CM8QL4KoCPAJgD8Kwx5hFr7blbaPeKtfaezfb+AMAXAXxG+oWdlDz9OYA/A/DtG372RwB+bK19aHPF9EcA/hGAVQAft9YuGGPOAPghgJHrv2SM+TUAtyhetLBCYRYWzluu8UmQ6egzisJTaaI2OV/kE9jTq7KTQq/CsYr1x0KF54OEyVdSm+h1Af7QrSkWaX0kDBsjH0gaDHFZMNab8uM1W5PPcyDI+zxKPsRYPgAAXJyRFwPeWd5G+HH5ozIe5o9vizi5XMnz4laXy3IbAcXCmMkNNDr7GJlZ+xSKugyR1hyO8vHRS4qsaRixqE8+zpljy7QNf0I+UFPheX9sRX7ozq7y8dFKywvOaVIYEQAyAflaNJJK1u0dywcIqzXgVWjPl4lMdTDE32F3pmTXIo2DF0N2nRNrk3lZ0sQIQICTTaukPgQAVMiig+UuAJyQYMU1NYQok/f1+jkJxN6k6Q53eVq1sgtY1Mv7fK/jeoTiLcT9ACattVMAYIz5LoBPAHjdgsIYMwHgO9hYC/xAaC8BhV3bjkmerLU/BfBGcf8nAHxr8+/fAvD3N/d90Vp7PZzwGoCQMSYIAMaYGID/GcCf7tS5Ojg4ODg4ODg4OOwErPLPm8ADm7Kk/9cYc+fmz0aA10kP5nADSX8DvgLga9bad+O/rA94dFPydAUb3+D/nJ3IW52UPWCtXQQAa+2iMab/Jvt8EsCL1trrQbv/DcA/A0CzOo0xnwXw2c1/wevdWh4TIJZDGpcn5sKjIPUpU8mYTgC4RDLWik1NZEAeyrk2Z93CPvliGOsC8FW8pvr4muJ6t3serBIyAOSbJGJD6J0hBYs9QPzsMxEetl4niYhzZDvAkzevLcthbQB4mfAfmgRiQ6ZkzTMZJzKhHKk/AwD1ttzGmRQfxwPEva1X4XjGnMaqClmdhzC7bTLOASAUlfss2qdwI4vITPf70nysH8vKjOnZdS6vYM+tRgLG3Oo0LHbIK08Q6wrZC4vGabxLVsn8MNDHa+HExuVOjfTy2g09y/InQuq4IrOboDjF3y35vBxJKxAXQgC4RKTOJZL47WE6aABeIz/7GlfGqaL8Uh9T1MAaJOYTzR3UCr2VuIUIRa8x5rkb/v2wtfbhLfZ9AcAha23ZGPMxAP8RwHHcXIF+szN4Hza+uQHgLwB86YZtN0qePgXgYQAPSie+p1yeNldXXwLw0c1/3wPgmLX2HxpjDrPf3+z0hzd+12utULGLOTRpHiYmL12u8S/owbA8MWjO42hcXv2Q2nkAgPkKkc4ogllRInka4t+lKLaYgwqf0J9blT+iagqddLVLXvgKTe9daXkyzYTkGSZBpCYAcMcJ2dokOMAH0MCK/MIfyfKXQr4s39ygsLi/jmZXbiNPxgbA85b6FBKOAPmYqyvyDtaJZXSR6KwBIOaXn+ueIP8w0TgOMdyXlj/UrsxxqVF3Tu73iX5e/CyckueojsLZhn3Madxx2OJZY5M60GIF9vi7I0HkjhMKNmqd5Olo9P7XqvLH71Kdzx8fJvai0WHeH8kj8pztTSmkM+T9kvTxRXw0JxfQ61XI+2JL8uKH5XosVvh8+xiREGo+gJPEuVEjvVoj5FxYkcez17ERfVBfx6q19r6bbTDGfA7A72/+82M3KHtgrX3UGPMvjTG92IhI3JhAOQpgq6RizUviEQDfZDu91S5Py8aYIQDY/P9//hoyxowC+EsA/8Bae2Xzxw8AuNcYMw3gcQAnjDGPvaVn7ODg4ODg4ODg4PAmcTtcnqy1X7XW3rP5Z8EYM2jMRjjKGHM/Nr7p1wA8C+C4MWbCGBMA8GlsLAreiCc2twHAbwuHfj+AK8J2AG99hOIRbGSJP7T5/78CAGNMCsBfA/jH1tonru9srf0agK9t7nMYwPettR/SHUoubMekRsdinB3OB1lRIL48j5M7cEeca2uY//oCSf4FgHm5Lhn6QryNd6Tlp+GuJE/OOzog19TwBzlTVavITNSFlV7axt8syWw5c4sBFF7iZHjE/HwMtmsyJxC7g0s4/PfKD0N4apW2kbwiM8ytC5y7uJtIax5f5cxvmsiijiueazapa2RCflKHoqhQX1wjVi4JP2dcO7ehPCuryzGoeK6zJZkxfXya1zph0EQXWGE7jZSRuQUd5vnDVJZZVUjzKkRWVyDRBwAokYvxx/g7rEtkqAs1/ry8dFWWvQyu8Do2mqKVDCESFfZ4eX/USeK2TxF9ChEzBYawQlbFlEQpYj4A8HmMzWEAUOnIjWiMNPY6LHbM5em/AfDfG2PaAGoAPm2ttQDaxpjPY8PgyAvgG9ba127y+18A8B1jzBcAfO8N244aY17ChnyqCeD32MnspG3svwXwIWzoweYA/BNsLCT+vTHmdwHMAPj1zd0/D+AYgD82xvzx5s8+aq0lpWocHBwcHBwcHBwc9ijeRI0JVbPW/hk23FRvtu1RAI+S37+KDSXQdTy0+fNpAAqR+uuxYwsKa+1vbrHpwzfZ909BXJw2L1BVgwIAPB4fIsGtK2WzapUatqtKvMKJLTYAbrumqZkQ98iMB6vYDACHSFVvTTI0Y6rSYU7/xQdljaovxXWIobx8nCNNnuD3fpL0NllRVEFvyf3hI1rsxRpnmdLLslVissD73AzKCdOew1wjH47JeRgn/LyWRZnUkLhjkI/ji0vyuU5V+BzJrHYjPv4sMGvRiEIXXO/IE0iZjC8AWCe1CjSW0iyxW8MMsyiHxtKTnWlTUYG4RuZsjeZbw9wyNAlJrYmUWDLfthRfMKwui2beZ/2uqUWwRBj1qQrPw2C1PYbD249Oat6lWRJ9uh0688GQfC2aatzs3ipuPY3Ca+79GuR3x1z3PD+RfQBNXZj9jj2VlO3g4ODg4ODg4OBwULALdSh2BW5B4eDg4ODg4ODg4LBDeBusJw7ugsLaLprtrUNpRSIXWFN4q8+QROZlTWYduQU9AS57YTaGVUWYNhOU29DY1zLv9KuFBG2j8ZrcH+kY95pnyNW47IX1WUJVbVtuo0xsUI9GefJepSnLhErPFmgbiaScCA8iiQK4bCo0we9baE6WRbUm+bWc9mXlYyzxa1mpKQqAEDDZw4yieDB7akOK2TtK/OhzRBIFAG1Skbla5/K/hYqcUF9VSEyJKzXWGryNSwV5Tj6ksFplUyGTMwFAnUhS2go6k83JBcWJpImxSIrYqwNAm2hjSor84mxd7nf2vgYA4mAKQ+ouAECbyrc4WK0bTS0cdusuFeVrYc8KADRIlvBilfd5pS2f6FqbJ9N3jNwhbasoqLIP4CIUDg4ODg4ODg4ODg5vCjvo8rSncGAXFNa20Gi+sZL4L8DsFDVVnWukwFWJ2KEBwCs5eZ9qm7Ppg2QXTXSBJdYtVjk3MxyRaZHZKmd+1xbliMwdiRRt466kzIo0u5y+Ycl3RU3SPmGi2AQzU+XRqTJJHq9Pbm1McB131GRb2ORREsEA4DsiR59MjF9Ld02+b/nL3CY1V5CZ8EqLT3lTJOFeUdcOZWLp2UuKGgKcyfQryhiPR+TnNqtIDm+SZyGV4NGnM2GZZawoDAhYxe6Ah+JL5SUAACAASURBVFskN7ryvdXM+4TUxwhJmAWAdVLYkNkfA9yyU8PIR8n9PxLj77ATCbmQW4AU4AOAmaJcwVzzLdYi8/pKg/fHNLPhVhgy5HntO0Ub21MMRBWRJRZrm6lwZ4CGle9tWxXTkTHgOUH3WcETdJ/dhotQODg4ODg4ODg4ODi8OVida9Z+xwFfUGzNNjD9MbN9BAB/Ql7hpwI8usDYzqKiONHjJZlJOBzlkYFqW2YSNA/DSl3ujwQnmKnV7sty/bTN48jXm/RzxqzMLIG9vEN6AnKfUrtFUrAQ4JGU53K8ytbPV+V97rjKKbdMQN6n3uF+nK2uXNxqTlGgUWM/yhAm93a6wqNTjEEcDPPzPBmXx2lIYSnNWLGO5Q9lgBwndZyz2P5jsr0x9Z8E0Lok2z0P5WWmHADunZfn5GcWeERvrib32Zk0P48IeV7mCGMPcKvVRoffW2aB6zN8jKWi8vsnM0iSDQFMJOR721zn42NxXh5jhxVz0Im4PMecK8oFGgEgT3LjNDk2KRKhypCAHouiAcA0yeMajfDvhiaZYK7V+L2HlZ/JmOV9vtdhocu/2e844AsKBwcHBwcHBwcHh92Di1DsY3iMH6Hg8Jbbg4QR0zCdJcJEDEV4G3clZHanrtD7P7Umr/B1umD5WjQPw3t75QONKArb5Vsyq3atylnqbEOmZ2oK1yvmwJRVGE+8t0fmJJihTNLPtdgJv8x0DrV4f63U5T7XnEfcz3KB+FSTbcjnsVhXOK+V5T7/rwf5w8CY/1lFbgtj7jTFrRhprymyxQp0thRRMIbaAm/DN0aK4/VzBzj/PfJY9hV4LofHL0cP7m7yAoxHSGQg6OPPS++AzNz29HFmt29RZuTLbe5oxsZYRzE+XlruFbffrSiyNjIm37vYCTk3CgBO0IAMf/ZtQy6y9kslOd8MAGxTnj+6dc5VN5YJ839Vvrev5UhEEECaFDWcJ/kkAGDJTGbAI+Tn6rIzX/gARCgAF6FwcHBwcHBwcHBwcHiTsLDovA2ysg/sgqJrm6jWZ7bczm5tSKGRZ7UbQqQuAwAMRmRnG4W0GKWWzEZcKG3fW13jA86Y3aCXM0QREpHRWK/xiAzv1ADRoGruSyYgs/ZRBfPP0BeTx8+RBHdoqhJXoxeW+mgbe2WujBF3E01NFnZvIwqnlzIJxj3DiU6aYxNRmM1ngnIbGqeoVFAOx7UV9R9mvi9vT6a3duS7jui43O+dEr8v67OyLny5zNnQ2aocER4M8fBlh0R1YiGet5QnkZIayQMDgOGwPAdFFHP2ZFk+j9U5npfy8cisuD3j4fUMPGn53lqSJwgAaMj9YVXlh+R+94T48xIaksfyoa6cTNgg7n8A8MSq7JgYV+Q8lsh3QY3ZaQLIeVbE7ZOtSX4i+wB75BW5oziwCwoHBwcHBwcHBweH3YTF3iHddhIHeEFh4DFbL7ErxF6p2Np+nYEs8aIHgCZxnggrWGymcz0a4ywTY/6nypzxYJrusEJbnCTsXo+C/ZsnVXkvlnleQZHkUJjbwDfUCYukieiMvEfWHvuO8LodqUVZN4yfyRpXAPB4ZCZqIcc18udK269QzcZxTvFcrxDGfYWnAlEnF00lW59H3ilb5+5KdZK7Mhbjz3Wa1HUJ9/DnukiKnD92cYy2kZySj6Opc2NIbtx8jfdHlLw1NdHLCyV5jooqHLxYtG2tyQfZIZLnlyC5UQAwQCwTJ8v8M+M/XBgXt6ev8P5YJrlzR6I86sMiMqzuDwDkSa2bvqCitkdKfmBYTZbFGneYnCFpOgHFQC4QF8pL7UXaRtLKOTiHvUdoGz/Ci3SfXYV1CwoHBwcHBwcHBwcHh23Avg1ETwd6QSHdQMYgMi9pAJivyKyJV7HC95I8i/ExXnjh0ISsky+scLbiYrZH3J5t8DaYo8xwH/dnT99N3HGITzgA3JWT++P9l/iD/eLUkLj9ZVKRGQBChO1iLNNATOHhzRBWVCC+V773o3cpcj3ysql5/zmeNDB+Tvain1yWzxMAnid1N1TWfYTY/UAfZxhZ/syioqbGk6vy9HwoxtsYIcOUVeMGgGBU3skX5/NcOCz3R1jByPtJFEwjb18nLDbLWwGAYVL5eTDEQ1hhryxQXyOOZwAQ88lXXFFEyJmLYL7JxxirVdEX5Hfmckk+j6uWRwbGyFjPKipl+0l18ZKiTxtkDBVbfE7ONmTWvkWOUVeMY/bs1xVOl3MVOerTBp9gYlaes+M+RTLHHoeTPDk4ODg4ODg4ODg4bAudt0EhigO+oNiaGWmR5SLTyQLAyaTMAmi01kvEMeRUgg/CwKjMIgV7+Ym0X5HZYU3F1PWmzCQUCjzKkSjIUQxNhMI7LDMeMZASoQDGV+W8gpKirgKLPoW8MnvTUdQgqUzKx4h5lmkb3g/LbJg9LkdrAABGPlffHdzfv2/sgrjd/5jsBgIAhzLyOJ5Z5/7sk2WZ6tQw0L0RObel1eWVkI/G5TGW8vNnMhOQx9gCqUECAL4IicT289yFdFvus8QKj/owtjxOIgcAZ+3LCge4Q6Qy9JFeHlWu1eVreW09TdtgjGfMp8gHIVHUkxnFtZDaQbbA86eOxOR+10Sw0n5FwSWCEsmR0OQVMD8fUvIJAI8+rZBIW5E/Thgir+MCTzmBj/RHT5tHlXMe4ljVUZzIPsDbYD1x0BcUDg4ODg4ODg4ODrsDC1fYbl/DGC/8vq2rSa4Rv+mZMmfuiLkFfIZTEbNES708yStN9jVkxr1Z5kz3lZzsBlQgzhUAsN6UWZNX1njl1vP/SWbmjhH3CwCYuFNmqTu8oC7WiEuGptJxlvjEeyBv7ypSKIYbchv9BR6NGQrKkQHPCV7LAv3k3nb5dGq8pOqqQtMbDMnPdUjBYjPXtHWFrryHVIXvD/NBGCA5A30kCgIANfLc5lo8UuJhNVnG+XMdOCafxwN3EqcxAK2LcrStPKOI6JXk52U+z/sjQ+5tZkwREa7L+2jG+nRBjrYNhngbzCkqHuOueqOH5Xt3ws+jHO2ifK65OR4FWy/JNUQuKCIlzAXOp4gusPyFwSCfg1gNETbSWY4FwJ0uWY0JACh15FBIRHDavI61t8WnNmB3KERhjPkQgH8BwA9g1Vr7wc2fPwjgKwC8AL5urX1I0VbZWhszxhwGcB7ARWwU7qoA+B1r7UXp9w/sgsLBwcHBwcHBwcFhV7FDtrHGmBSAfwngQWvtjDGmf/PnXgBfBfARAHMAnjXGPGKtPXcLzV+x1t6z2d4fAPgigM9Iv+AWFA4ODg4ODg4ODg47gA3J045EKH4LwP9jrZ0BAGvt9UTD+wFMWmunAMAY810AnwDwugWFMWYCwHewsRb4gXCcBAAaajzACwoDI1jAhYi8IubnIcM2CWHdkeCWaeMROaT8woqcMAsAIPscT3A5AbM4fWadJ1QPh+TQJbPSBICARz6PF1e5vCJ8Se733hEuAzrcJz87+bkB2kacFIVitrEFhbSGRVHPLvPx86P/Sz7OkSiX1vRFZuXtGd7nDC9cG6H7LBO7TZbMCAAlYhnNiucBwGhEnlrHh7kM5GiU2A7z4YFOTb6W1AKX5xAnTaCPJ7rbQ6PyDlFZrgIAvg/KYyi9wq2J06tyvw88OUPb6BTkARA8w2VToYx8vdEVPmcnf7Ykbh/L8T7NVmUDAo8iGdqblJ8pTw9/d/jjshQtzHzeAfTPyPf2VIjbllPTjwCfP8CkzjX+HmzNyMUkc1Nyf11Y4vN+lSSgX61qCsDK51Fs8YTqsJXHYMTy8bPXYWFvxeWp1xjz3A3/ftha+/AW+54A4DfGPAYgDuAr1tpvAxgBcONLeQ7Ae27y+18B8DVr7beNMZ97w7ajxpiXNtuNbPH7r8MBXlA4ODg4ODg4ODg47C5uIYVi1Vp7n3JfH4B7AXwYQBjAk8aYp4Cb2tXd7AzeB+CTm3//CwBfumHbjZKnTwF4GMCD7GQOJKxto9Xa2qrSS1gEFn0AuCbuWExmGQBgJCUzUQFFkuDjq/I+ST9f4TNb2EyA98cRcr2jikhJndixXqvwa5ktyP0RDnPWpEaS5SsdzlT1keTNkE+OpFQV1rRdkkDMEnsBblFYJLaQAFAvyf3x0hq3wWSJiJr5eKEmRx41VohJMtY1CY/nSAJo2M+jl8k6sZ5t8THoJ1aaTcU4Zhmg9vwcbcJU5UisPX6YtmFTsnEEwnxuMMRK1XeIR45wVZ7HOvPcTcEXl5OMTZInIcfH5OM0Gzyhmt3/comfR+cl+aEyhj90mXvlc/UO8/eg7w7Cykf5tSBOquOFFW0wu942j7YEjsnGIr1JOSI8+jh/11aIzTsreggAxxLye/LldT7Pecg7rODhRiz7AbdD8rQZRfj9zX9+DBuRh1VrbQVAxRjzUwB3b/587IZfHQWwsEWzmhN7BMA32U4asxoHBwcHBwcHBwcHh1vERqVsq/ojtmPtV62192z+WQDwVwA+YIzxGWOuy5LOA3gWwHFjzIQxJgDg09hYFLwRT2xuA4DfFg79fgBX2HUe2AgFYNG1W2sVa22ZlU34+VorRIiI/iiPUPQfllmmZEHhcUpwmdjpAQBxkEO2wVlZxqhHIpypCnZkRiOW54w7K0y2PsO1oSz6dLHEWftBMkBahAHS1FBaJ7axzBYSABokMpAjTBbAi4rNVjkTXiXnoXHJuJCX9cl39/Apry8oHyilKKDF+v1bV/ppG0Vi23hvhj8LSXKuOWL1DABH3imzpbbImfDK96bE7YGUvB0AAqdIhEKhb+8uysxt4SV+b9fXSAQ0xOe5yJRc6DGQ4Pe2sCiz5Y9dG6ZthEnu3D19vCDl0rrcH8+ukfsG4MyynB9zdIhbV8f6Sc4aCT4AgCdK8kHifC40bBwGt//ZZZvy3MAi1wDwck7OfZqv8efpaolHIBhCVh7HLSiq9O0D2B1IyrbWnjfG/ADAK9godfF1a+1ZADDGfB7AD7FhG/sNa+1rN2niCwC+Y4z5AoDvvWHb9RwKA6AJ4PfY+RzgBYWDg4ODg4ODg4PD7mKnqm1Ya78M4Ms3+fmjAB4lv3sVwAM3/OihzZ9PYyMn45ZwYBcUXk8YiciJLbcvtmWm6nSXuwmlA/IQ8Sr064Fj8j0LKmjqM1654FN8hl/Lubys+dZEbCIkJyDzDs7+eUgxpvc8u0jbuLjYI24vaXICrHy9LDoFAF6PfC1+Mj7yiujCvYfl/oiNcAapuS6PsbOT3NGKRcHKbT6OGX+jKbTE0KPJBYrKuS+DioJy7Nn3Gp5T8syaPMjWmnx8sMiRJgrmCZNIWh+PgAYLMsu4/Ap/dzXPytdSqmteZ/I8p3FWGySR50Qfd86qrMuRxblFXtA0W5OZXU1U8HhcHqeaqHI8IV/vCikSCgCvkFzBx1d5Ubqwl7guxvl9SQXkaFs8qIg+kQhVrszHKY1eQ36nLyv6/G+Xt/+Oyzbl/pozcq4HAFxrPCVut3b/F77bcHna/9fBcGAXFA4ODg4ODg4ODg67jR2qQ7GncGAXFBYW7e7WTMGxmKwfbCoE203i9pJTsASHfDLbZY700TZiAVnneiTMdbD5V2RmLt/iLGSAeJb7TvFrwfFxcXPfBzjL1DcrR2waT3Ov+XMvyOc6W+W64ERQZm8iQZm1jZI6FgCQOiOPU+84j075iX75WJnrl4NEi+013KVlidSI8Cvo9I6Vp7QxUvcFABKkXsrYCHcCMiR4kKtzt5gieeZSfs54DYXl6/XUZaYcADwRQlVGOKvvCckd0lQ4VtVIZLHS5pHHlbp8rsUWfyWeGpbrXYQPKdy3YvJ9ubbK55cCOdfeIB8fp9Jyfkz6OJ+DLEnAC8zy8xglznsaVz2WD8T6CwCGY/Jc6CfzHAA0mvJx0gr3Rw+Jbper8nNbKvEIVyogz6eaiHDEQ/pU8Q2dCh0Wt8c9PN/sYmOaH2gXsYOF7fYUDuyCwsHBwcHBwcHBwWG3YXcsi2LvYFcWFMaYaQAlAB0AbWvtfcaYXwfwJwBOAbjfWvvc5r4fwUaiSAAbmeZ/aK39CTuGBx4EfVuzohNxmc04Htu+e8FClUco7lqT2V/fu7h21EyMidsjE1vZD/8C97RkR7D1lw/RNkJe0mcaz/uQzLzYXjk/AgAwKDMaQb/C6eeyzEIfqXDLEFZnwkfYrnqbs9i1q/IkFepyD2/vkMyE9/4Kjwz0NmTW7e4cj3Kwa7l0hVd/fWZNjjz6SHXyjX2IrnxU0caQ/Oy/M8ZzgRaemhC3n0jwyr+ZmJzv0VY48JgwYf69Cnelutyn59Z4JC1BInbrCjeyJKn/0Sa5UwAQihE3oQFFzQSffF/oXAqgRubTjsLph0VJfeM8Mg2/fB73Vfj7Z3FKfs+tKaL9cZ8cfUoFFPWHFPl1DGwEFYqKeV1Rg0g8hiLixz5va8z6EUCIPPuHW7LiYAPyPgs2q2hjr8O6CMUO4+9Ya2+MHZ8F8GsA/vUb9lsF8HFr7YIx5gw2bLBG3qJzdHBwcHBwcHBwcHhTcJKntxjW2vMAYN5Qwdpa++IN/3wNQMgYE7TWiiLULrpodrau8ZAmbi/MHQUAlhty951Ocq1k+RLxvL9DzgcAwKt3JjljFjkhszuHJnn110RI1gW3XuZteKZkJtt7hDOZOHNU3n5oiDYx8iuyttj/kyV+HgTlihyNyZMaEwDwxGuj4vbRa7zPj56S+9w/wlk7T1I+V88g1/RGSGXxIw2eC3SxyMc6g4alZmCVjkN386n34/6r4nbfAL8v3SJhus/SJmBrMottFBWI/ffKNREe9HE3mPq8zKlahZOYl9QYmb8qR7gAIJCR2zDD3MHLm5IjnEeP8flltCRHH6cWFHMlgUkrijecPiJujryX35ejc/J77tAz12gbnQJxNCM5AwDQrcv3trrCmf9KSZ4LAyRyDQAhEikpNuT3dUKRXxUlFb07QT4PGtKlXsPzq6I+4jZV5+/rl+keuw2Ljtm+6mWvY7cqZVsAf2OMed4Y89lb+L1PAniRLSYcHBwcHBwcHBwcdhvXIxSaP/sZuxWheN+mhKkfwI+MMRestT+VfsEYcyeALwH4qLDPZwF8FgC8JoSEf+uVbW9AZjM0essW0agO93KNsy8sMwmr3+Pa89RJWWPoO8zzMGxD7o8uOLtTJox6Y4Wz5a0Z+YGqPcP7dPjTpEL8GHeNYMycz8+dftpEx8pqFTSJFzkAVImO+gKpLwIAF56U92kRNzMAOJ2S78voAM/lCETkMVguch11uS33WavLGTP27FfneH9EQ/L1+sb5fQneS/KFAnz69tbl6MIA+DiuXpS3xw7z5xq9JLfll4/RJmKEUdXkcqAou/hMPMsjJV25hBEQVdSDOiRHbKJHuKo3elk+18iTK7SNwpw8Z3cX+XzrGSbPdi+PlNiTcpTDe+dx2ga9+8x6DQBa8vMSLPD+SJM20FRUfq6QWjcrcgT9nS/L0U0AeN8kqWOyzqN15wpy5DmvyOVokWBK3K/Ia+GfSbuO7tsgKXtXIhTW2oXN/68A+EsA90v7G2NGN/f7B9baLb8WrbUPW2vvs9be5/FsP7nKwcHBwcHBwcHB4c3DKuMT+3vR8ZZHKIwxUQAea21p8+8fBfC/CvunAPw1gH9srX1Cexwv/IibrZloliPRq6iGy+ouxAZ4lCM4ITNE3qtc3fXqz+SaCSdXuEuCh8j1Y4qITZW4rPhTPJwX8Mj3ZfZ5Rf2HH8vMXOyDPD+GIZxSVKAuy+MjmpL7lEV8AKBO/MZZxW8AWCQVhpM+PsldKMiM+1OrXFeeYM8kcaQBAD/xbz9EqmADwFBSZrHDQ7w/uoS0L/2tzDACQLcjR0I0hKsvwvIOeButuswyVn/C87w6DfmZjJ7iryLPOBlDSYXePyhHqDSRo8arclTHvsajHIbVdxiXIxgAaKTVP8lzjuIt+f3S5gZNaF8+L27vKgj52EcH5R3uJHlxAGyU3P82PxFTIXmPne2/OxBQkJ0sL5Js91cUFc7X5XkuXuZtZALyBMLqAgHAlfJuKe/fOlgAXeIeeBCwG3dyAMDjxpiXATwD4K+ttT8wxvyqMWYOwAMA/toY88PN/T8P4BiAPzbGvLT5h2tWHBwcHBwcHBwcHHYZXeV/+xlveYTCWjsF4O6b/PwvsSFreuPP/xTAn97ycWDRNlszEhHChmpWWm2icQ/dyZ1tzIS8NgoFuNtH4IJ8LYVl7sJSrcnM3fkcjwycSMlaWg2j2iGBoaailsXz52T98f3BedqGl9ivL05zJnNghImtZcyWuQd8qS33h1EkeXlJbYZsk9+4NCHd8k2ed7BOKswuEVc1ACi25OOcjHOG0c/mhigfg7Ymvxh+fl525wJ4Zd8MqegNAD3EeS2jiMT6Se0GFkkBgMkFOR8k+xqfowwZpx88w52AovfI+Q3tZd4fLSKj967xKFh3Ws7zCtyrmDua8n1ZepbnC4XCJGegxUNYawvye+7CGo9OnpyXoz7J9FO0jTaplF2p8P64tC6fa5CoEgAg6pP7dLyPRyczZ+R+90TluaF+hUcXfv6aXL/qcplHyBdq8ruhY/n7p0ymsXpnfycqAxvfox0cfJenPWMb6+Dg4ODg4ODg4HCwYNHFbZDL7XG4BYWDg4ODg4ODg4PDDmG/J1xrcGAXFAYGfrt1yC7klVeLcUXyJhseppdLnphdnunnlnsnsy+I2/MXuUSjViQJ1URuAABNJr8JcmmEj0RZw0R+AQCVtnwti1d48bNwSI7DLle4HKm3JSe9WTKAMkGekM8kLR6F5KlEiij9bJVfa8Ajh77biqi1nyirSorkThYeX1Mkug/U5f7waGrnETvoI0luPzlFEt27xLYaAHLkeqcVsrpfefe0uN2f4ucxVpflkKuL/L5UyPyyMMttLscjstykuspfiaGkPAdppJ21ZXkn+zS3fGW63CurPLH77qOypDY0wi+mPyjPcxrJ04/nB8TtXkVyOLO3nqnyaxkMyc9tD7GbB4CITx5DU1f5M+eZlrcnSHE8jeX4ApnnnszyD+B8c/slwZLEFjYZVNhB73FY2LdFUvaBXVA4ODg4ODg4ODg47Dac5Gkfo2VrWGy9uuV2A9mmzkPsJ1Wo8cQoxOUoRjfFk6F975cT2jI9nN5JLsmVYQYmeZIgS3rzH+EMIrN+PD3Gz6M1JV9L6Rof9itrMg1dJWwpwCMQHnIazL4UAEY/RJL3mNUmAJuX+/Q9L/Ik9ty8nOy6WuSs3DnCyK8rksMZWDFKAPARm1xPj8Ke1CMfZ2icW3o2puQBElNEsBJJOdKay/FrCQySAo19vJBbIiuP5ViWv2ynyfyyVuOJ3ZkVmQ0tFnkbg0n5eTFxnvwbHpKTv5uKQl3Nsjw+Km0+z1WK8rlGGnyM+eLyWB+NKQqaEkb9apX36VpDPo+En7/TB0PyfMoMLACg3iFmLYrE7jwxqAh75WtlCgwAaHXlZ8Fr+FwZI9GYVpf3V4EUAmx0DwKzb98WkqeDbwDs4ODg4ODg4ODgsAuwsOjYlurPrcAY84c3lFM4a4zpGGMym9seNMZcNMZMGmP+SNleefP/h40xtc12XzbG/NwYc5L9/oGNUHiNH3H/1hrSZldm3epEXwgAhbqs+60/zws+he6Ti87ZO+6gbXQ/8IC43TM4SdvwnJsSt0dzXNMbjJL8hj5ulWnvOUUOwrXW/pLMhvacvUTbiPxoTtw+sMYjJTXCqLZIlKPd5ut9EyPM3XAvb+OkHCWL3MNZykhdjsaNzPPiindemBa3zzzNoxxTeTkKRgIHAIBWi0Sf0jw3Chk52hJZIwW0AKSIhWk4wiOgsVH5mfSH+Dj2xOVnTpMrFhqSr3d0lp9HOihHWwLE7hcAvCT65FVEpv298iDyDPAkG19TPte87CqrgoYPjSbkMeS/k+fwgbDQx7s83DK2LOe2nFnhkbTX1uRzvR3sKbPpBoCBkNynLNcDAEjwgF7Lcl0R0SERX41Fbo6M41nwb6Cj3iFx+0hEUQiQB3x3HXYHJE/W2i8D+DIAGGM+DuAfWmvXjTFeAF8F8BEAcwCeNcY8Yq09dwvNX7HW3rPZ9h8A+CKAz0i/cGAXFA4ODg4ODg4ODg67C/tWFK37TQD/dvPv9wOY3Kz7BmPMdwF8AsDrFhTGmAkA38HGWuAHQtsJALK2Hgd4QdG1bVQ7Wy9bc0SjmK5pXEfklfOLL8h5GgDw3h+/KG73eDkj0h2Uj2OTnDEzhGUyt2Gk2CVe0MdcIcWpEgrnrCQpOndygrYRDsgX7PmbadqGLydPID7iKNIo8Xufe4zohhc5IeF7z7i8Q4bn8SBCtOcjffw8SPhgcIWzXbVL8jOZI1FFACgyJ6iawtkkLPeH5/7jtInRdxFGK6Bg7ggCJa5vxwKh/8b5POc7JT9zR39Nwd7ViPOeRmvdkNnj1HmeL9SaJlGMQc7qe07Iz1z/e7Z/Xz768ixtos7qpob58wJyb/0f4Dk2fnLvEiTqDACHV8n3DhvHAOAjc64ixGlzcjTO1rlTYbcgj9PGgtxf01N8DGabcrHJhJ9fa518A6XAVQnJoBwpGVKkrO11WNySbWyvMea5G/79sLX2YekXjDERAA8C+Pzmj0YA3DgBzAF4z01+9SsAvmat/bYx5nNv2HbUGPMSgDiAyBa//zoc2AWFg4ODg4ODg4ODw+7Cwlq15GnVWnvfLR7g4wCesNZe1xfebDV4MybkfQA+ufn3vwDwpRu23Sh5+hSAh7GxaNkSB3ZB0e5WsVrcuj7DevPvir8fqfJl8QLRKZ5O8gSbxR8T3+upn9I2AnfIEQhzXNYoAgCCMtPAHIsAYJ3oXH3Pc+/9zs9lLXWtxFnZ/r9PIjInCSMPACQy5Alz9qazIu/TbsiPX6POH89SRWbCL/6Yu9b0/FyOHBlDI50YPiTXGQiO8mgL8+/vKvLVmNPPxRJ/rk8lZHa49SKjdQE/czdRRGwQJcwuEFFP7AAAFTNJREFUqf0BgDOuGlafXUuB5z+wiI2NKmjItMIljsDk5HGKAL+3HTm1RdWnNIrKtgMwVTlSZsIaYbl8rnaV31uzRuaPtKI/iNuhHeZRMPSTZ+qQIupDYBT31pAomGnzCIWnIg8y32U5kpbJ8hytd9bk+eWQIneh0ZHfcRpXvRUS8FUYRe0L3A7J02YU4fc3//kxa+11C89P4xdyJ2AjIjF2w79HAWxl96np4UcAfJPt5FyeHBwcHBwcHBwcHHYAFhZd21L9Edux9qvW2ns2/ywAgDEmCeCDAP7qhl2fBXDcGDNhjAlgY8HxyE2afGJzGwD8tnDo9wOgVhEHNkIB+ODzba39zrfktVTEy7umSNpIKHziGZ5+hlc7Hb0gs0ij7+CuRmzxvDrLHXYqTTlis77AWch8RWZNpko8h+Le/yA7UvXf9RJtg2HlNc78M7cgVuk4r/DVv0oqHc/XOMsU8JBaKLQFYPWqXOk2pfCAT/nlI/kVDjyT5e1XVZ2Iym2snOP3pXNWZkPjCc4e+wLbZ7T8MbnPvEnOIDYW5e31Mte3+/xXxe2RIX6t3h55LBtNRV3Curan+bU0i/K87/vJZdqGNy3ninlGeDSGafVbK1xi0azJ77nV/4+/w5qPyg6BVsFSD9xJGPnDfN43UeJspKG62T6KNmyHjGVFfQdDcjW6xCUuzBwXAQxF5Tkq6uNOUdm6PBfO1ngbiySYUmkfhBDFjiZl/yqAv7HW/ucbaq1tG2M+D+CHALwAvmGtfe0mv/sFAN8xxnwBwPfesO16DoUB0ATwe+xEDvCCwsHBwcHBwcHBwWEXYXErORS31rS1fw7gz2/y80cBPEp+9yqAG+sOPLT582kA3E3hDTjAC4oOOp2t2aY6ubca7V/IK6+cExHiSgIgEpP1lkM1rvt8fLFf3D6Q4y49cb/MaLBKpgCvHn1virN/fX55n6yCtf/JjJwz8t46Z4eDAbk/rqzxPi205MerQ8bYGnEiA4BMQB7ICjIMZ/PyTgOKaYVFIJb4o4AQqf7aUhBVrE87ijZSAfmZTPbyi2mTqr1Tc7LDCgA8tSaz1AoTFhyLyczviKKKcSgoh+G9Hs68LZPK86+d54x8lVQgPq2oLH/HhFwPpVXnUQ5Wy6JT4IMsf1HeJ5zidX98ZCqcu8z7NEtyBdMhPtZb5L68muPnsXBZ7vc5RfoDm6c0zz5DJsAbifrkfVj9BwA4FJHfP2MRUhtGMTdkiePdsqIW18WSfC1XijzxbSIuH+cIqcS+P/D2qJR9gBcUDg4ODg4ODg4ODrsHC8BqnG32OQ7sgiLq7cM7Yp/ecjvjGYIKvXbYK7PDA/cr3Bz6ZeYuvsRZt5E52bkkt8gp5tWirMVnzC8ApIPyA5M8xCv7WrLLRI24tACI+uVrWSR5BwBgb+q69gusNzl7wzT/Sb/M3qRJlAQAfEbu8ygZowDgN1znysCidXXCYgJAi0mPFR7wXiOfR0ghs0+HZVY2dIhfi63LFzNU4e4595KooCZq2EOuZanC85ru6pPrfwSTfIzZOfnejbLaHwAWSW2gy2QOA4DgNflcfYrqwCODsquRV8GoBgrysz07naZthMn8oZnnGAb7uTNfqyE/VOUWn186Vh6HKUU4brEuPw8hxTudRRf8ChsblmYxFubzOqumfbUs91fSz59Jdoy6oqJ3iQQg6h3F+8cjv0vZPdkfsDtSKXuv4cAuKBwcHBwcHBwcHBx2G90uX0judxzYBYWFRcdsvSJk/slZwroAQA/Rr3vv4g5N9swJuY0cry4dfvaiuD04zozTgYG2XGugfo0zdy3CEAXfyXXjaMvH6a3zmgiRnBzmiCjqgzQq8v1/5iq/t4wtZ4T7A++fo8fw9crsXyfHr7VdlM/zmRdHaBs9RGu9QjzPASDqk881oGCPl6ryca5VOVua6ZEF275jvAotq0WQrijyeELyC8ij6I9Qj7xPZo771cePE6eoAe7A0xeWI62RBR69zKzJx1lRRFvSJKekS94LABDuk/vUpyjtG7HyefQ3eQTLQ6KCQ53tO57Fjypcjdryczve5FHlTFjujzmFu19vUP6cKRHXPQBIkFzCmqJPWRssMgDwdwNTDExWFBXOCRb5ZwMipDsyAT7fGqIG8KjKJOxt2J11edozOLALCgcHBwcHBwcHB4fdhsuhcHBwcHBwcHBwcHB4c7B2x2xj9xIO7IKiiw7KRgq1yoW44opEoDhLfArzsKPt7ZW3Z7i8wuORpUbedS6bshe3qsq+gaDCvjbQJv1xeoKfx6B8X6J/h0sjYmtEFnVWLsQEAOE5ORnxg6kZ2gYjJOpF+fHzH+d2i+aXzsjb41wq4C+Qa83xxEyUFb6ODAX53namuNzt5IxsC9os86xKWmRtQrYlBgD4ZC1AsMalaGz2MP7tS1oCR7gtqKeHJAj38nEaJHKUwDGuL04W5DF2rKoYpwRlPjXAPyzLOMwoT6j2+eRxmM7wea5bIdKaBteshOPyOPSd7qNtMIxMKDyj6/L1HsuR6ooA6rPy+8e2udSIFYLUwLLaePzWolWVx0eXmFzUqtw0ZK0kS/M0MtXVhnwcjZmL18hjcCCk6LB9AGcb6+Dg4ODg4ODg4ODwJmGd5Gk/o9Et4UrlsS23d9JyMrTGMo3BXlmi+3jiF+Q2Do3RNrpjo+J2k1Yw3XHZYtCfnqdtdKY5g0xBmF34OGtix4ldYh9PDvcuyFaZkfPXaBudBTmxMhwk18qoLgAoyaytIcnBAGCjpL/Ct1ww878EiaIBgKnI1+KN8qKG4R55DAYWeSSFMpkBzv7ZEZK0r3iubVC+XutTTN/k/pvVVd7GNdkcwB5TRB4fkO2xVeOjKTOVnhaP+oCMsdSsHKkFAJTkRHb7jpO0CZuQ52TTUVhGX5sVt/cNyGYdAGCCJIF8TC6aCgC2X46yq+YPMpa9bd4f0UZD3kExxhAkcUH2fgK4b6xiTga5FkOiyrjGx/Hwkpws31nk7/PWKinyWOPfUYVVeZ6rkyjIfoAF0LXO5cnBwcHBwcHBwcHB4U3BRSj2Naxto9namn3LNWUWYYw7/1ELudnv8wHU9+pL4vbg+Gu0DU8/0ckfGaRtwE9YgCrXMbazMkPoVeQu4Mnz8jHmuc2l/16icT+s0MATFqlb4Lrg1qLMSBhSuM5bUDCu86+Im9s5Pga9UcIiKQIlXmJfa5I8uoAYYQcZ8wegPS3bky68wot99Y3JbfhfvkLbMFnC7g1z5hcs/0XDlpK8JsNYXQDwyscxK3LeCgCARQ801/JWIKgo8liQx4cp8WKklC33K86Dnasix8a2SN7bOZ4rZvLE4jZFolMAEJVfuJZsV0EToWBQzEG3Bex5YFFSzXmSfWybt6HJB2FoNOXP0K4iD2M/wC0oHBwcHBwcHBwcHBzeJCzgkrL3MyysoFlbIS4rMwqd9CxxUgh7uVY/mUuI25ef4k5RacJ03z1+mbYRG5Lb6CiK3MxMpcTt3rMa2zR5SF4r8iJriSfke3v62Au0jSAJYtTmOGuyuiwzc4329pkZS/aZUhSEYoWW8oqCUA3Shsbt45f7ZFY/FeFRofWqrOeeKvEIRSYn69uHphSOZ16ZtS83eLGvc3l5bngxz6fvXxuVtdbvfEDOFQIA4yVFQM/xOWoyK7vVNbucPR6Nk8iRh7+wx99F2HQFiV2clJ8HX4Dr16slObrQ/x4+V3qScr83L/FISXFOPg9N8cROW34usyyCoUA8zCNpPq/cZ36/Ilrrk/fRpLUx+AL8PPwReR9/L5lPFd+upavyOJ5c4FHUYlP+BmopnmsPKQDbR4qm7gtYF6FwcHBwcHBwcHBwcHiTsHC2sfsaxvgR8G9d06BCXDTqHY2zgLyy/jlxLwCAtpVZpqUqH4QR4pDx3WuHaRuVlnyceoefx2hU7rPAbZBJl1ucIhoIy3rbs3nO2idJjRELzrj/0qjsnR6Pyazbq/OcIVquywxjSMEwltryjcm3tq89riuCU/96UvbvJ0Q5AE4w94R4IyNhuT/OFrev576mkNmvNeR7F1bM3o+vylGO1cd4dOFURo4chYI814exkPkWn2/nVuSIb8rPXVRe/ZE8xurE3x/gc0NdwcqW2/I+mQV+LSw6WWjx+eOBQTmSlkzy0HSWzKdXijyHokr6g5TtAADMVOUHoqn4nuuQ14sm0lohuQc+w9sIeeU2QrfhXVpsbT834YlVOQJaNjya+1vDco5nleSq7g9YWKvIidznOLALCgcHBwcHBwcHB4fdhXN52tfweoJIh7f2Rx+LyNEDVsoA4GzoqsJAZZBYdPeHODVTIkyDhtVvdOQ2uoy6AXC1LF/wBHPxARDzy+cxEN4+u5NQaGkHQvK11BWsSTwtt8Gqsh4q8cq/jY6ct5Jv8Ue8zu69QjfsJ8NUE104IZPpCHj4iaw2th9NIUMQo2HONEWYntvwZ8FLXGl6eRMIkT7TMPIskhYIczY9kpf3iZL+Ajirr2GPWTROg2Gf3B8ZxbUs1uT3z7Uqd3kaCsl9WlXcWxblUJDpNPqkmT/YuZLUBhUSfoVLHMkF07zT5yvy/Y8qwi3poHwesxX5Wqpt3mHsPDTpIgkPc+bjbbDotWaO2h9wCwoHBwcHBwcHBwcHhzcFC7gIxd6BMeZBAF8B4AXwdWvtQ9L+HngQ8Gyt7Sw25WXxXIV3DcsJyBENNABYEudoKuidbE0+TsjHaSYvoaI07hY9QVkHnQjw8+gLygfyEjZsYx95+3Kds5Rhr3wtfsV5lPMyexOsywxjucFZyquEyZyp8D5nwaeAh7dxrSxfy1CE93mUjFMWBQGAPKkvo+G6VglzpxmDLEIRV1CudcKm5xTsMbPv1+QC5QpyI76yhpGXQ7EvkWcFAEokMOT38DE2TtxzIoqco6W6fK6a8cFYV02krd2V56iYYozNExe4CnHxAYClqjw+pip8HlsmRj4kxQ8An/eZmx0AFEiihWYuDHnle6doArPkmQqSY8QVkyWLguQVNSaGIuSdr4iQs08czX3bD7CqmM+twRiTBPBvAIxj43v+f7fWfnNz2y19M2/+TtlaGzPGHAZwHsBFAAZABcDvWGsvSr+/L2JJxhgvgK8C+LsATgP4TWPM6d09KwcHBwcHBwcHBweGrvLPLeFzAM5Za+8G8CEA/8wYE7hN38xXrLX3bLb9LQBfZL+wXyIU9wOYtNZOAYAx5rsAPgHg3Fa/EEQEJ+07tmywTSh35tQA3J6V8xzRW+YaXJ9c7BJNr4+7TeXbchtxL2eZWoRqKClyOUAYU0UqBxKEVFtR2Fov1eU+GwzxB39ycpQfSMBiTZM/wxxF+HGKpI2VGqeqCl3ZDSbkJQkSAJaJo1lXwfCwSJpmuvYSplsT4WLRBc15ZGvys99r+fQ9TzijXJMPkMlyn7hdkx/DXK3WGjzKUe/I+wyGOZvO8oVaXX5ve0gwRcNAzxENfIVVsAbQG5bvbdfy+eOVvJwsGPdzRzwWFdTM2SyAmW8onn0yPyQUrD2LQJQVoZIqGadx4soIAD5yHkHSX5qIzlJV7q9Ck397RElF72KLt1Fuy98WVfLM7g/sWFK2BRA3xhgAMQDrANrA/9/e3YVaNsZxHP/+FElxY0SGpMlLXjIXjBhN4y2T3I0akgslkZe5UVyh3JhSUkQTk6hRaqS5wMzkYsiNkYZBkaHQKG95OZlozN/FXtNszDl7nzVz9j57ne+ndmc9Z62993+f/ufp+bef9TxcyhBj5iRnAhvp1QJvzvA+JwAzL/fH5BQUi4Fv+trf0vuD/UuSO4A7muaf235Z9/EIYpNGbRHw47iDmI3tg/dxmz9mXklTc2fi8loakrk9jc0Dh6lDOeOIvMrc2QL7Zt519aBjk7zf115fVeunufYpYDOwBzgeWFNV+5MMNWamNyXqmap6Mcnd/zm3JMnO5nWPm+b5/zIpBcWhStT/ldfNH309QJL3q+riuQ5MGjVzW11kXqurzO2FrapWzdFLXwfsBK4ClgDbkrzDkGNmYDmwujl+CVjXd253VS0FSLKG3th6xs8xEfdQ0KuuTu9rn0avIpMkSZI6LcndSXY2j1OB24BXq+cL4CvgXGY3Zh5mLvpmYMWgiyaloNgBnJXkzCTHADfR+4CSJElSp1XV082N0kurag/wNXA1QJKTgXOALxl+zPxucw7glhne+gpg96D4JmLKU1XtS3IPsIXeElgbquqTAU+bbs6ZNOnMbXWRea2uMrc1Fx4FXkiyi940pweq6keAIcfMa4GNSdYCm/5z7sA9FAH+Am4fFExqmA0GJEmSJOkQJmXKkyRJkqR5yIJCkiRJUmudKyiSrEryWZIvkjw47nikNgblcZKVSX7tW/HhoXHEKR2uJBuSfJ/EfYM0sQblsX22uq5T91A0241/DlxLb9msHcDNVTXtjtrSfDNMHidZCdxfVTeMJUjpCEmyApgCXqyqC8Ydj9TGoDy2z1bXde0bimU0241X1V/Age3GpUliHmvBqKq3gZ/HHYd0OMxjLXRdKygOtd344jHFIrU1bB5fluTDJG8kOX80oUmSWrLPVmdNxD4UszDsduPSfDZMHn8AnFFVU0muB14DzprzyCRJbdhnq9O69g3FbLYbl+argXlcVb9V1VRz/DpwdJJFowtRkjQs+2x1XdcKimG3G5fms4F5nOSUJGmOl9H7X/5p5JFKkgayz1bXdWrKU1XtG3K7cWnemi6Pk9zZnH8WuBG4K8k+YC9wU3VpyTYtGEleBlYCi5J8CzxcVc+PNyppdg6Vx8DRYJ+thaFTy8ZKkiRJGq2uTXmSJEmSNEIWFJIkSZJas6CQJEmS1JoFhSRJkqTWLCgkSZIktdapZWMlqUuSnAi81TRPAf4Gfmjaf1TV5WMJTJKkPi4bK0kTIMkjwFRVPT7uWCRJ6ueUJ0maQEmmmp8rk2xP8kqSz5M8luSWJO8l2ZVkSXPdSUk2JdnRPJaP9xNIkrrCgkKSJt9FwFrgQuBW4OyqWgY8B9zbXPMk8ERVXQKsbs5JknTYvIdCkibfjqr6DiDJbmBr8/tdwJXN8TXAeUkOPOeEJMdX1e8jjVSS1DkWFJI0+f7sO97f197PwX7+KOCyqto7ysAkSd3nlCdJWhi2AvccaCRZOsZYJEkdYkEhSQvDfcDFST5K8ilw57gDkiR1g8vGSpIkSWrNbygkSZIktWZBIUmSJKk1CwpJkiRJrVlQSJIkSWrNgkKSJElSaxYUkiRJklqzoJAkSZLU2j8M8SLGLk8LbQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 864x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plotting Mel Power Spectrogram\n",
+    "S = librosa.feature.melspectrogram(aa, sr=sample_rate, n_mels=128)\n",
+    "\n",
+    "# Convert to log scale (dB). We'll use the peak power (max) as reference.\n",
+    "log_S = librosa.power_to_db(S, ref=np.max)\n",
+    "\n",
+    "plt.figure(figsize=(12, 4))\n",
+    "librosa.display.specshow(log_S, sr=sample_rate, x_axis='time', y_axis='mel')\n",
+    "plt.title('Mel power spectrogram ')\n",
+    "plt.colorbar(format='%+02.0f dB')\n",
+    "plt.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 864x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plotting MFCC\n",
+    "mfcc = librosa.feature.mfcc(S=log_S, n_mfcc=13)\n",
+    "\n",
+    "# Let's pad on the first and second deltas while we're at it\n",
+    "delta2_mfcc = librosa.feature.delta(mfcc, order=2)\n",
+    "\n",
+    "plt.figure(figsize=(12, 4))\n",
+    "librosa.display.specshow(delta2_mfcc)\n",
+    "plt.ylabel('MFCC coeffs')\n",
+    "plt.xlabel('Time')\n",
+    "plt.title('MFCC')\n",
+    "plt.colorbar()\n",
+    "plt.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
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type=\"audio/wav\" />\n",
+       "                    Your browser does not support the audio element.\n",
+       "                </audio>\n",
+       "              "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.Audio object>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Original Sound\n",
+    "ipd.Audio(samples, rate=sample_rate)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "                <audio  controls=\"controls\" >\n",
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type=\"audio/wav\" />\n",
+       "                    Your browser does not support the audio element.\n",
+       "                </audio>\n",
+       "              "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.Audio object>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Silence trimmed Sound by librosa.effects.trim()\n",
+    "ipd.Audio(aa, rate=sample_rate)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "                <audio  controls=\"controls\" >\n",
+       "                    <source 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type=\"audio/wav\" />\n",
+       "                    Your browser does not support the audio element.\n",
+       "                </audio>\n",
+       "              "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.Audio object>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Silence trimmed Sound by manual trimming\n",
+    "samples_cut = samples[10000:-12500]\n",
+    "ipd.Audio(samples_cut, rate=sample_rate)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Defining the label"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1440"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# 2 class: Positive & Negative\n",
+    "\n",
+    "# Positive: Calm, Happy\n",
+    "# Negative: Angry, Fearful, Sad\n",
+    "\n",
+    "label2_list = []\n",
+    "for i in range(len(data_df)):\n",
+    "    if data_df.emotion[i] == 2: # Calm\n",
+    "        lb = \"_positive\"\n",
+    "    elif data_df.emotion[i] == 3: # Happy\n",
+    "        lb = \"_positive\"\n",
+    "    elif data_df.emotion[i] == 4: # Sad\n",
+    "        lb = \"_negative\"\n",
+    "    elif data_df.emotion[i] == 5: # Angry\n",
+    "        lb = \"_negative\"\n",
+    "    elif data_df.emotion[i] == 6: # Fearful\n",
+    "        lb = \"_negative\"\n",
+    "    else:\n",
+    "        lb = \"_none\"\n",
+    "        \n",
+    "    # Add gender to the label    \n",
+    "    label2_list.append(data_df.gender[i] + lb)\n",
+    "    \n",
+    "len(label2_list)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1440"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#3 class: Positive, Neutral & Negative\n",
+    "\n",
+    "# Positive:  Happy\n",
+    "# Negative: Angry, Fearful, Sad\n",
+    "# Neutral: Calm, Neutral\n",
+    "\n",
+    "label3_list = []\n",
+    "for i in range(len(data_df)):\n",
+    "    if data_df.emotion[i] == 1: # Neutral\n",
+    "        lb = \"_neutral\"\n",
+    "    elif data_df.emotion[i] == 2: # Calm\n",
+    "        lb = \"_neutral\"\n",
+    "    elif data_df.emotion[i] == 3: # Happy\n",
+    "        lb = \"_positive\"\n",
+    "    elif data_df.emotion[i] == 4: # Sad\n",
+    "        lb = \"_negative\"\n",
+    "    elif data_df.emotion[i] == 5: # Angry\n",
+    "        lb = \"_negative\"\n",
+    "    elif data_df.emotion[i] == 6: # Fearful\n",
+    "        lb = \"_negative\"\n",
+    "    else:\n",
+    "        lb = \"_none\"\n",
+    "    \n",
+    "    # Add gender to the label  \n",
+    "    label3_list.append(data_df.gender[i] + lb)\n",
+    "    \n",
+    "len(label3_list)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1440"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# 5 class: angry, calm, sad, happy & fearful\n",
+    "label5_list = []\n",
+    "for i in range(len(data_df)):\n",
+    "    if data_df.emotion[i] == 2:\n",
+    "        lb = \"_calm\"\n",
+    "    elif data_df.emotion[i] == 3:\n",
+    "        lb = \"_happy\"\n",
+    "    elif data_df.emotion[i] == 4:\n",
+    "        lb = \"_sad\"\n",
+    "    elif data_df.emotion[i] == 5:\n",
+    "        lb = \"_angry\"\n",
+    "    elif data_df.emotion[i] == 6:\n",
+    "        lb = \"_fearful\"    \n",
+    "    else:\n",
+    "        lb = \"_none\"\n",
+    "    \n",
+    "    # Add gender to the label  \n",
+    "    label5_list.append(data_df.gender[i] + lb)\n",
+    "    \n",
+    "len(label5_list)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1440"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# All class\n",
+    "\n",
+    "label8_list = []\n",
+    "for i in range(len(data_df)):\n",
+    "    if data_df.emotion[i] == 1:\n",
+    "        lb = \"_neutral\"\n",
+    "    elif data_df.emotion[i] == 2:\n",
+    "        lb = \"_calm\"\n",
+    "    elif data_df.emotion[i] == 3:\n",
+    "        lb = \"_happy\"\n",
+    "    elif data_df.emotion[i] == 4:\n",
+    "        lb = \"_sad\"\n",
+    "    elif data_df.emotion[i] == 5:\n",
+    "        lb = \"_angry\"\n",
+    "    elif data_df.emotion[i] == 6:\n",
+    "        lb = \"_fearful\"\n",
+    "    elif data_df.emotion[i] == 7:\n",
+    "        lb = \"_disgust\"\n",
+    "    elif data_df.emotion[i] == 8:\n",
+    "        lb = \"_surprised\"\n",
+    "    else:\n",
+    "        lb = \"_none\"\n",
+    "        \n",
+    "    # Add gender to the label \n",
+    "    label8_list.append(data_df.gender[i]  + lb)\n",
+    "    \n",
+    "len(label8_list)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>path</th>\n",
+       "      <th>source</th>\n",
+       "      <th>actor</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>intensity</th>\n",
+       "      <th>statement</th>\n",
+       "      <th>repetition</th>\n",
+       "      <th>emotion</th>\n",
+       "      <th>label</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male_none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male_none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male_none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male_none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                path source actor gender  \\\n",
+       "0  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "1  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "2  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "3  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "4  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "\n",
+       "  intensity statement repetition emotion      label  \n",
+       "0         0         0          0       1  male_none  \n",
+       "1         0         0          1       1  male_none  \n",
+       "2         0         1          0       1  male_none  \n",
+       "3         0         1          1       1  male_none  \n",
+       "4         0         0          0       2  male_calm  "
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Select the label set you want by commenting the unwanteds.\n",
+    "\n",
+    "data_df['label'] = label5_list\n",
+    "# data_df['label'] = label3_list\n",
+    "# data_df['label'] = label5_list\n",
+    "#data_df['label'] = label8_list\n",
+    "data_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Index(['male_none', 'female_none', 'female_calm', 'male_sad', 'female_fearful',\n",
+      "       'male_happy', 'male_fearful', 'male_calm', 'female_happy',\n",
+      "       'female_angry', 'male_angry', 'female_sad'],\n",
+      "      dtype='object')\n"
+     ]
+    }
+   ],
+   "source": [
+    "print (data_df.label.value_counts().keys())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Plotting the emotion distribution\n",
+    "\n",
+    "def plot_emotion_dist(dist, color_code='#C2185B', title=\"Plot\"):\n",
+    "    \"\"\"\n",
+    "    To plot the data distributioin by class.\n",
+    "    Arg:\n",
+    "      dist: pandas series of label count. \n",
+    "    \"\"\"\n",
+    "    tmp_df = pd.DataFrame()\n",
+    "    tmp_df['Emotion'] = list(dist.keys())\n",
+    "    tmp_df['Count'] = list(dist)\n",
+    "    fig, ax = plt.subplots(figsize=(14, 7))\n",
+    "    ax = sns.barplot(x=\"Emotion\", y='Count', color=color_code, data=tmp_df)\n",
+    "    ax.set_title(title)\n",
+    "    ax.set_xticklabels(ax.get_xticklabels(),rotation=45)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1008x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "a = data_df.label.value_counts()\n",
+    "plot_emotion_dist(a, \"#2962FF\", \"Emotion Distribution\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Data Splitting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "400\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>path</th>\n",
+       "      <th>source</th>\n",
+       "      <th>actor</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>intensity</th>\n",
+       "      <th>statement</th>\n",
+       "      <th>repetition</th>\n",
+       "      <th>emotion</th>\n",
+       "      <th>label</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>male_sad</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>male_sad</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>male_sad</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>male_sad</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>male_sad</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>male_sad</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>male_sad</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>male_sad</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>male_angry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>male_angry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>male_angry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>male_angry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>male_angry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>male_angry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>male_angry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>male_angry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>male_fearful</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>male_fearful</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>male_fearful</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>male_fearful</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>male_fearful</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>male_fearful</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>male_fearful</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>male_fearful</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                 path source actor gender  \\\n",
+       "0   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "1   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "2   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "3   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "4   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "5   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "6   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "7   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "8   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "9   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "10  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "11  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "12  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "13  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "14  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "15  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "16  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "17  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "18  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "19  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "20  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "21  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "22  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "23  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "24  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "25  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "26  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "27  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "28  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "29  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "30  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "31  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "32  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "33  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "34  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "35  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "36  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "37  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "38  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "39  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     1   male   \n",
+       "40  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     3   male   \n",
+       "41  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     3   male   \n",
+       "42  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     3   male   \n",
+       "43  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     3   male   \n",
+       "44  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     3   male   \n",
+       "45  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     3   male   \n",
+       "46  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     3   male   \n",
+       "47  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     3   male   \n",
+       "48  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     3   male   \n",
+       "49  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1     3   male   \n",
+       "\n",
+       "   intensity statement repetition emotion         label  \n",
+       "0          0         0          0       2     male_calm  \n",
+       "1          0         0          1       2     male_calm  \n",
+       "2          0         1          0       2     male_calm  \n",
+       "3          0         1          1       2     male_calm  \n",
+       "4          1         0          0       2     male_calm  \n",
+       "5          1         0          1       2     male_calm  \n",
+       "6          1         1          0       2     male_calm  \n",
+       "7          1         1          1       2     male_calm  \n",
+       "8          0         0          0       3    male_happy  \n",
+       "9          0         0          1       3    male_happy  \n",
+       "10         0         1          0       3    male_happy  \n",
+       "11         0         1          1       3    male_happy  \n",
+       "12         1         0          0       3    male_happy  \n",
+       "13         1         0          1       3    male_happy  \n",
+       "14         1         1          0       3    male_happy  \n",
+       "15         1         1          1       3    male_happy  \n",
+       "16         0         0          0       4      male_sad  \n",
+       "17         0         0          1       4      male_sad  \n",
+       "18         0         1          0       4      male_sad  \n",
+       "19         0         1          1       4      male_sad  \n",
+       "20         1         0          0       4      male_sad  \n",
+       "21         1         0          1       4      male_sad  \n",
+       "22         1         1          0       4      male_sad  \n",
+       "23         1         1          1       4      male_sad  \n",
+       "24         0         0          0       5    male_angry  \n",
+       "25         0         0          1       5    male_angry  \n",
+       "26         0         1          0       5    male_angry  \n",
+       "27         0         1          1       5    male_angry  \n",
+       "28         1         0          0       5    male_angry  \n",
+       "29         1         0          1       5    male_angry  \n",
+       "30         1         1          0       5    male_angry  \n",
+       "31         1         1          1       5    male_angry  \n",
+       "32         0         0          0       6  male_fearful  \n",
+       "33         0         0          1       6  male_fearful  \n",
+       "34         0         1          0       6  male_fearful  \n",
+       "35         0         1          1       6  male_fearful  \n",
+       "36         1         0          0       6  male_fearful  \n",
+       "37         1         0          1       6  male_fearful  \n",
+       "38         1         1          0       6  male_fearful  \n",
+       "39         1         1          1       6  male_fearful  \n",
+       "40         0         0          0       2     male_calm  \n",
+       "41         0         0          1       2     male_calm  \n",
+       "42         0         1          0       2     male_calm  \n",
+       "43         0         1          1       2     male_calm  \n",
+       "44         1         0          0       2     male_calm  \n",
+       "45         1         0          1       2     male_calm  \n",
+       "46         1         1          0       2     male_calm  \n",
+       "47         1         1          1       2     male_calm  \n",
+       "48         0         0          0       3    male_happy  \n",
+       "49         0         0          1       3    male_happy  "
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Male Data Set\n",
+    "\n",
+    "data2_df = data_df.copy()\n",
+    "data2_df = data2_df[data2_df.label != \"male_none\"]\n",
+    "data2_df = data2_df[data2_df.label != \"female_none\"].reset_index(drop=True)\n",
+    "data2_df = data2_df[data2_df.label != \"female_neutral\"]\n",
+    "data2_df = data2_df[data2_df.label != \"female_happy\"]\n",
+    "data2_df = data2_df[data2_df.label != \"female_angry\"]\n",
+    "data2_df = data2_df[data2_df.label != \"female_sad\"]\n",
+    "data2_df = data2_df[data2_df.label != \"female_fearful\"]\n",
+    "data2_df = data2_df[data2_df.label != \"female_calm\"]\n",
+    "data2_df = data2_df[data2_df.label != \"female_positive\"]\n",
+    "data2_df = data2_df[data2_df.label != \"female_negative\"].reset_index(drop=True)\n",
+    "\n",
+    "tmp1 = data2_df[data2_df.actor == 21]\n",
+    "tmp2 = data2_df[data2_df.actor == 22]\n",
+    "tmp3 = data2_df[data2_df.actor == 23]\n",
+    "tmp4 = data2_df[data2_df.actor == 24]\n",
+    "data3_df = pd.concat([tmp1, tmp3],ignore_index=True).reset_index(drop=True)\n",
+    "data2_df = data2_df[data2_df.actor != 21]\n",
+    "data2_df = data2_df[data2_df.actor != 22]\n",
+    "data2_df = data2_df[data2_df.actor != 23].reset_index(drop=True)\n",
+    "data2_df = data2_df[data2_df.actor != 24].reset_index(drop=True)\n",
+    "print (len(data2_df))\n",
+    "data2_df.head(50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "80\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>path</th>\n",
+       "      <th>source</th>\n",
+       "      <th>actor</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>intensity</th>\n",
+       "      <th>statement</th>\n",
+       "      <th>repetition</th>\n",
+       "      <th>emotion</th>\n",
+       "      <th>label</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>21</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>21</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>21</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>21</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>21</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>23</td>\n",
+       "      <td>male</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>male_fearful</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>76</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>23</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>male_fearful</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>77</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>23</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>male_fearful</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>78</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>23</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>male_fearful</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>79</th>\n",
+       "      <td>E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>23</td>\n",
+       "      <td>male</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>male_fearful</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>80 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                 path source actor gender  \\\n",
+       "0   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1    21   male   \n",
+       "1   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1    21   male   \n",
+       "2   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1    21   male   \n",
+       "3   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1    21   male   \n",
+       "4   E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1    21   male   \n",
+       "..                                                ...    ...   ...    ...   \n",
+       "75  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1    23   male   \n",
+       "76  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1    23   male   \n",
+       "77  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1    23   male   \n",
+       "78  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1    23   male   \n",
+       "79  E:\\8th sem\\Final_Year_Project_Files\\Audio_Spee...      1    23   male   \n",
+       "\n",
+       "   intensity statement repetition emotion         label  \n",
+       "0          0         0          0       2     male_calm  \n",
+       "1          0         0          1       2     male_calm  \n",
+       "2          0         1          0       2     male_calm  \n",
+       "3          0         1          1       2     male_calm  \n",
+       "4          1         0          0       2     male_calm  \n",
+       "..       ...       ...        ...     ...           ...  \n",
+       "75         0         1          1       6  male_fearful  \n",
+       "76         1         0          0       6  male_fearful  \n",
+       "77         1         0          1       6  male_fearful  \n",
+       "78         1         1          0       6  male_fearful  \n",
+       "79         1         1          1       6  male_fearful  \n",
+       "\n",
+       "[80 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print (len(data3_df))\n",
+    "data3_df.head(80)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Analysing Features of audio files using librosa"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|████████████████████████████████████████████████████████████████████████████████| 400/400 [00:16<00:00, 23.60it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "data = pd.DataFrame(columns=['feature'])\n",
+    "for i in tqdm(range(len(data2_df))):\n",
+    "    X, sample_rate = librosa.load(data2_df.path[i], res_type='kaiser_fast',duration=input_duration,sr=22050*2,offset=0.5)\n",
+    "#     X = X[10000:90000]\n",
+    "    sample_rate = np.array(sample_rate)\n",
+    "    mfccs = np.mean(librosa.feature.mfcc(y=X, sr=sample_rate, n_mfcc=13), axis=0)\n",
+    "    feature = mfccs\n",
+    "    data.loc[i] = [feature]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>feature</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>[-70.26777, -70.26777, -70.26777, -70.26777, -...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>[-67.55739, -67.55739, -67.55739, -67.55739, -...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>[-69.67329, -69.693306, -69.693306, -69.693306...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>[-69.0514, -69.0514, -69.0514, -69.0514, -69.0...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>[-73.84137, -73.84137, -73.84137, -73.71965, -...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                             feature\n",
+       "0  [-70.26777, -70.26777, -70.26777, -70.26777, -...\n",
+       "1  [-67.55739, -67.55739, -67.55739, -67.55739, -...\n",
+       "2  [-69.67329, -69.693306, -69.693306, -69.693306...\n",
+       "3  [-69.0514, -69.0514, -69.0514, -69.0514, -69.0...\n",
+       "4  [-73.84137, -73.84137, -73.84137, -73.71965, -..."
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df3 = pd.DataFrame(data['feature'].values.tolist())\n",
+    "labels = data2_df.label"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
+       "      <th>...</th>\n",
+       "      <th>249</th>\n",
+       "      <th>250</th>\n",
+       "      <th>251</th>\n",
+       "      <th>252</th>\n",
+       "      <th>253</th>\n",
+       "      <th>254</th>\n",
+       "      <th>255</th>\n",
+       "      <th>256</th>\n",
+       "      <th>257</th>\n",
+       "      <th>258</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-69.957710</td>\n",
+       "      <td>-68.377602</td>\n",
+       "      <td>-69.862564</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.122139</td>\n",
+       "      <td>-68.554955</td>\n",
+       "      <td>-70.206528</td>\n",
+       "      <td>-70.267769</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-65.239815</td>\n",
+       "      <td>-65.536194</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.126572</td>\n",
+       "      <td>-67.557388</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>-69.673286</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.620773</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-68.906570</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.383514</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-68.754860</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-68.359085</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-65.446953</td>\n",
+       "      <td>-68.552094</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-68.688614</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.719650</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.303635</td>\n",
+       "      <td>-72.806808</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 259 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         0          1          2          3          4          5    \\\n",
+       "0 -70.267769 -70.267769 -70.267769 -70.267769 -70.267769 -70.267769   \n",
+       "1 -67.557388 -67.557388 -67.557388 -67.557388 -67.557388 -67.557388   \n",
+       "2 -69.673286 -69.693306 -69.693306 -69.693306 -69.693306 -69.693306   \n",
+       "3 -69.051399 -69.051399 -69.051399 -69.051399 -69.051399 -68.754860   \n",
+       "4 -73.841370 -73.841370 -73.841370 -73.719650 -73.841370 -73.841370   \n",
+       "\n",
+       "         6          7          8          9    ...        249        250  \\\n",
+       "0 -70.267769 -70.267769 -70.267769 -70.267769  ... -70.267769 -70.267769   \n",
+       "1 -65.239815 -65.536194 -67.557388 -67.557388  ... -67.557388 -67.557388   \n",
+       "2 -69.693306 -69.620773 -69.693306 -68.906570  ... -69.693306 -69.693306   \n",
+       "3 -69.051399 -69.051399 -69.051399 -68.359085  ... -65.446953 -68.552094   \n",
+       "4 -73.841370 -73.303635 -72.806808 -73.841370  ... -73.841370 -73.841370   \n",
+       "\n",
+       "         251        252        253        254        255        256  \\\n",
+       "0 -69.957710 -68.377602 -69.862564 -70.267769 -70.122139 -68.554955   \n",
+       "1 -67.557388 -67.557388 -67.557388 -67.557388 -67.557388 -67.557388   \n",
+       "2 -69.693306 -69.693306 -69.693306 -69.383514 -69.693306 -69.693306   \n",
+       "3 -69.051399 -69.051399 -69.051399 -68.688614 -69.051399        NaN   \n",
+       "4 -73.841370 -73.841370 -73.841370 -73.841370 -73.841370 -73.841370   \n",
+       "\n",
+       "         257        258  \n",
+       "0 -70.206528 -70.267769  \n",
+       "1 -67.126572 -67.557388  \n",
+       "2 -69.693306 -69.693306  \n",
+       "3        NaN        NaN  \n",
+       "4 -73.841370 -73.841370  \n",
+       "\n",
+       "[5 rows x 259 columns]"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "newdf = pd.concat([df3,labels], axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "400"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rnewdf = newdf.rename(index=str, columns={\"0\": \"label\"})\n",
+    "len(rnewdf)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
+       "      <th>...</th>\n",
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+       "      <th>252</th>\n",
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+       "      <th>254</th>\n",
+       "      <th>255</th>\n",
+       "      <th>256</th>\n",
+       "      <th>257</th>\n",
+       "      <th>258</th>\n",
+       "      <th>label</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-69.957710</td>\n",
+       "      <td>-68.377602</td>\n",
+       "      <td>-69.862564</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.122139</td>\n",
+       "      <td>-68.554955</td>\n",
+       "      <td>-70.206528</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-65.239815</td>\n",
+       "      <td>-65.536194</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.126572</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>-69.673286</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.620773</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-68.906570</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.383514</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-68.754860</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-68.359085</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-68.552094</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-68.688614</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.719650</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.303635</td>\n",
+       "      <td>-72.806808</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>-69.243256</td>\n",
+       "      <td>-69.243256</td>\n",
+       "      <td>-69.243256</td>\n",
+       "      <td>-69.243256</td>\n",
+       "      <td>-68.901970</td>\n",
+       "      <td>-67.983002</td>\n",
+       "      <td>-68.089203</td>\n",
+       "      <td>-67.897331</td>\n",
+       "      <td>-65.258011</td>\n",
+       "      <td>-67.170975</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-57.185970</td>\n",
+       "      <td>-61.188725</td>\n",
+       "      <td>-67.108391</td>\n",
+       "      <td>-67.508125</td>\n",
+       "      <td>-66.245537</td>\n",
+       "      <td>-68.733047</td>\n",
+       "      <td>-69.243256</td>\n",
+       "      <td>-69.243256</td>\n",
+       "      <td>-69.243256</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>-73.254967</td>\n",
+       "      <td>-73.254967</td>\n",
+       "      <td>-73.254967</td>\n",
+       "      <td>-73.254967</td>\n",
+       "      <td>-68.774429</td>\n",
+       "      <td>-69.380402</td>\n",
+       "      <td>-73.254967</td>\n",
+       "      <td>-73.254967</td>\n",
+       "      <td>-73.254967</td>\n",
+       "      <td>-73.254967</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-50.884079</td>\n",
+       "      <td>-55.666733</td>\n",
+       "      <td>-54.600010</td>\n",
+       "      <td>-53.439114</td>\n",
+       "      <td>-56.300125</td>\n",
+       "      <td>-57.458267</td>\n",
+       "      <td>-58.767071</td>\n",
+       "      <td>-59.836510</td>\n",
+       "      <td>-58.409870</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>-70.746513</td>\n",
+       "      <td>-70.746513</td>\n",
+       "      <td>-70.025284</td>\n",
+       "      <td>-69.131271</td>\n",
+       "      <td>-70.746513</td>\n",
+       "      <td>-70.746513</td>\n",
+       "      <td>-70.746513</td>\n",
+       "      <td>-70.746513</td>\n",
+       "      <td>-70.746513</td>\n",
+       "      <td>-70.746513</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-70.746513</td>\n",
+       "      <td>-70.746513</td>\n",
+       "      <td>-70.079247</td>\n",
+       "      <td>-69.590454</td>\n",
+       "      <td>-69.202751</td>\n",
+       "      <td>-70.159462</td>\n",
+       "      <td>-70.445366</td>\n",
+       "      <td>-68.199043</td>\n",
+       "      <td>-67.414200</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>-63.311062</td>\n",
+       "      <td>-63.072487</td>\n",
+       "      <td>-63.412422</td>\n",
+       "      <td>-63.796757</td>\n",
+       "      <td>-63.581989</td>\n",
+       "      <td>-58.921223</td>\n",
+       "      <td>-57.955044</td>\n",
+       "      <td>-61.224972</td>\n",
+       "      <td>-63.782932</td>\n",
+       "      <td>-63.796757</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-63.740608</td>\n",
+       "      <td>-62.410255</td>\n",
+       "      <td>-62.489079</td>\n",
+       "      <td>-62.494453</td>\n",
+       "      <td>-62.632626</td>\n",
+       "      <td>-62.824276</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>-60.369045</td>\n",
+       "      <td>-60.083717</td>\n",
+       "      <td>-60.978924</td>\n",
+       "      <td>-60.952457</td>\n",
+       "      <td>-60.982483</td>\n",
+       "      <td>-60.983948</td>\n",
+       "      <td>-60.981255</td>\n",
+       "      <td>-60.981255</td>\n",
+       "      <td>-60.981255</td>\n",
+       "      <td>-60.249615</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-60.981255</td>\n",
+       "      <td>-60.981255</td>\n",
+       "      <td>-60.981255</td>\n",
+       "      <td>-60.981255</td>\n",
+       "      <td>-60.981255</td>\n",
+       "      <td>-60.981255</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10 rows × 260 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           0          1          2          3          4          5  \\\n",
+       "0 -70.267769 -70.267769 -70.267769 -70.267769 -70.267769 -70.267769   \n",
+       "1 -67.557388 -67.557388 -67.557388 -67.557388 -67.557388 -67.557388   \n",
+       "2 -69.673286 -69.693306 -69.693306 -69.693306 -69.693306 -69.693306   \n",
+       "3 -69.051399 -69.051399 -69.051399 -69.051399 -69.051399 -68.754860   \n",
+       "4 -73.841370 -73.841370 -73.841370 -73.719650 -73.841370 -73.841370   \n",
+       "5 -69.243256 -69.243256 -69.243256 -69.243256 -68.901970 -67.983002   \n",
+       "6 -73.254967 -73.254967 -73.254967 -73.254967 -68.774429 -69.380402   \n",
+       "7 -70.746513 -70.746513 -70.025284 -69.131271 -70.746513 -70.746513   \n",
+       "8 -63.311062 -63.072487 -63.412422 -63.796757 -63.581989 -58.921223   \n",
+       "9 -60.369045 -60.083717 -60.978924 -60.952457 -60.982483 -60.983948   \n",
+       "\n",
+       "           6          7          8          9  ...        250        251  \\\n",
+       "0 -70.267769 -70.267769 -70.267769 -70.267769  ... -70.267769 -69.957710   \n",
+       "1 -65.239815 -65.536194 -67.557388 -67.557388  ... -67.557388 -67.557388   \n",
+       "2 -69.693306 -69.620773 -69.693306 -68.906570  ... -69.693306 -69.693306   \n",
+       "3 -69.051399 -69.051399 -69.051399 -68.359085  ... -68.552094 -69.051399   \n",
+       "4 -73.841370 -73.303635 -72.806808 -73.841370  ... -73.841370 -73.841370   \n",
+       "5 -68.089203 -67.897331 -65.258011 -67.170975  ... -57.185970 -61.188725   \n",
+       "6 -73.254967 -73.254967 -73.254967 -73.254967  ... -50.884079 -55.666733   \n",
+       "7 -70.746513 -70.746513 -70.746513 -70.746513  ... -70.746513 -70.746513   \n",
+       "8 -57.955044 -61.224972 -63.782932 -63.796757  ... -63.740608 -62.410255   \n",
+       "9 -60.981255 -60.981255 -60.981255 -60.249615  ... -60.981255 -60.981255   \n",
+       "\n",
+       "         252        253        254        255        256        257  \\\n",
+       "0 -68.377602 -69.862564 -70.267769 -70.122139 -68.554955 -70.206528   \n",
+       "1 -67.557388 -67.557388 -67.557388 -67.557388 -67.557388 -67.126572   \n",
+       "2 -69.693306 -69.693306 -69.383514 -69.693306 -69.693306 -69.693306   \n",
+       "3 -69.051399 -69.051399 -68.688614 -69.051399        NaN        NaN   \n",
+       "4 -73.841370 -73.841370 -73.841370 -73.841370 -73.841370 -73.841370   \n",
+       "5 -67.108391 -67.508125 -66.245537 -68.733047 -69.243256 -69.243256   \n",
+       "6 -54.600010 -53.439114 -56.300125 -57.458267 -58.767071 -59.836510   \n",
+       "7 -70.079247 -69.590454 -69.202751 -70.159462 -70.445366 -68.199043   \n",
+       "8 -62.489079 -62.494453 -62.632626 -62.824276        NaN        NaN   \n",
+       "9 -60.981255 -60.981255 -60.981255 -60.981255        NaN        NaN   \n",
+       "\n",
+       "         258       label  \n",
+       "0 -70.267769   male_calm  \n",
+       "1 -67.557388   male_calm  \n",
+       "2 -69.693306   male_calm  \n",
+       "3        NaN   male_calm  \n",
+       "4 -73.841370   male_calm  \n",
+       "5 -69.243256   male_calm  \n",
+       "6 -58.409870   male_calm  \n",
+       "7 -67.414200   male_calm  \n",
+       "8        NaN  male_happy  \n",
+       "9        NaN  male_happy  \n",
+       "\n",
+       "[10 rows x 260 columns]"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rnewdf.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2284"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rnewdf.isnull().sum().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
+       "      <th>...</th>\n",
+       "      <th>250</th>\n",
+       "      <th>251</th>\n",
+       "      <th>252</th>\n",
+       "      <th>253</th>\n",
+       "      <th>254</th>\n",
+       "      <th>255</th>\n",
+       "      <th>256</th>\n",
+       "      <th>257</th>\n",
+       "      <th>258</th>\n",
+       "      <th>label</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-69.957710</td>\n",
+       "      <td>-68.377602</td>\n",
+       "      <td>-69.862564</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.122139</td>\n",
+       "      <td>-68.554955</td>\n",
+       "      <td>-70.206528</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-65.239815</td>\n",
+       "      <td>-65.536194</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.126572</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>-69.673286</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.620773</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-68.906570</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.383514</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-68.754860</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-68.359085</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-68.552094</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-68.688614</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.719650</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.303635</td>\n",
+       "      <td>-72.806808</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 260 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           0          1          2          3          4          5  \\\n",
+       "0 -70.267769 -70.267769 -70.267769 -70.267769 -70.267769 -70.267769   \n",
+       "1 -67.557388 -67.557388 -67.557388 -67.557388 -67.557388 -67.557388   \n",
+       "2 -69.673286 -69.693306 -69.693306 -69.693306 -69.693306 -69.693306   \n",
+       "3 -69.051399 -69.051399 -69.051399 -69.051399 -69.051399 -68.754860   \n",
+       "4 -73.841370 -73.841370 -73.841370 -73.719650 -73.841370 -73.841370   \n",
+       "\n",
+       "           6          7          8          9  ...        250        251  \\\n",
+       "0 -70.267769 -70.267769 -70.267769 -70.267769  ... -70.267769 -69.957710   \n",
+       "1 -65.239815 -65.536194 -67.557388 -67.557388  ... -67.557388 -67.557388   \n",
+       "2 -69.693306 -69.620773 -69.693306 -68.906570  ... -69.693306 -69.693306   \n",
+       "3 -69.051399 -69.051399 -69.051399 -68.359085  ... -68.552094 -69.051399   \n",
+       "4 -73.841370 -73.303635 -72.806808 -73.841370  ... -73.841370 -73.841370   \n",
+       "\n",
+       "         252        253        254        255        256        257  \\\n",
+       "0 -68.377602 -69.862564 -70.267769 -70.122139 -68.554955 -70.206528   \n",
+       "1 -67.557388 -67.557388 -67.557388 -67.557388 -67.557388 -67.126572   \n",
+       "2 -69.693306 -69.693306 -69.383514 -69.693306 -69.693306 -69.693306   \n",
+       "3 -69.051399 -69.051399 -68.688614 -69.051399   0.000000   0.000000   \n",
+       "4 -73.841370 -73.841370 -73.841370 -73.841370 -73.841370 -73.841370   \n",
+       "\n",
+       "         258      label  \n",
+       "0 -70.267769  male_calm  \n",
+       "1 -67.557388  male_calm  \n",
+       "2 -69.693306  male_calm  \n",
+       "3   0.000000  male_calm  \n",
+       "4 -73.841370  male_calm  \n",
+       "\n",
+       "[5 rows x 260 columns]"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rnewdf = rnewdf.fillna(0)\n",
+    "rnewdf.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Data Making/Processing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_time_series(data):\n",
+    "    \"\"\"\n",
+    "    Plot the Audio Frequency.\n",
+    "    \"\"\"\n",
+    "    fig = plt.figure(figsize=(14, 8))\n",
+    "    plt.title('Raw wave ')\n",
+    "    plt.ylabel('Amplitude')\n",
+    "    plt.plot(np.linspace(0, 1, len(data)), data)\n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "def noise(data):\n",
+    "    \"\"\"\n",
+    "    Adding White Noise.\n",
+    "    \"\"\"\n",
+    "    # you can take any distribution from https://docs.scipy.org/doc/numpy-1.13.0/reference/routines.random.html\n",
+    "    noise_amp = 0.005*np.random.uniform()*np.amax(data)\n",
+    "    data = data.astype('float64') + noise_amp * np.random.normal(size=data.shape[0])\n",
+    "    return data\n",
+    "    \n",
+    "def shift(data):\n",
+    "    \"\"\"\n",
+    "    Random Shifting.\n",
+    "    \"\"\"\n",
+    "    s_range = int(np.random.uniform(low=-5, high = 5)*500)\n",
+    "    return np.roll(data, s_range)\n",
+    "    \n",
+    "def stretch(data, rate=0.8):\n",
+    "    \"\"\"\n",
+    "    Streching the Sound.\n",
+    "    \"\"\"\n",
+    "    data = librosa.effects.time_stretch(data, rate)\n",
+    "    return data\n",
+    "    \n",
+    "def pitch(data, sample_rate):\n",
+    "    \"\"\"\n",
+    "    Pitch Tuning.\n",
+    "    \"\"\"\n",
+    "    bins_per_octave = 12\n",
+    "    pitch_pm = 2\n",
+    "    pitch_change =  pitch_pm * 2*(np.random.uniform())   \n",
+    "    data = librosa.effects.pitch_shift(data.astype('float64'), \n",
+    "                                      sample_rate, n_steps=pitch_change, \n",
+    "                                      bins_per_octave=bins_per_octave)\n",
+    "    return data\n",
+    "    \n",
+    "def dyn_change(data):\n",
+    "    \"\"\"\n",
+    "    Random Value Change.\n",
+    "    \"\"\"\n",
+    "    dyn_change = np.random.uniform(low=1.5,high=3)\n",
+    "    return (data * dyn_change)\n",
+    "    \n",
+    "def speedNpitch(data):\n",
+    "    \"\"\"\n",
+    "    peed and Pitch Tuning.\n",
+    "    \"\"\"\n",
+    "    # you can change low and high here\n",
+    "    length_change = np.random.uniform(low=0.8, high = 1)\n",
+    "    speed_fac = 1.0  / length_change\n",
+    "    tmp = np.interp(np.arange(0,len(data),speed_fac),np.arange(0,len(data)),data)\n",
+    "    minlen = min(data.shape[0], tmp.shape[0])\n",
+    "    data *= 0\n",
+    "    data[0:minlen] = tmp[0:minlen]\n",
+    "    return data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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4Nu0r1befm+vMztJYIodNAgCQikieAHhW/VN3Z07m31+x05H9eI1zuSsVJwAAIiF5AjKY3+/tykKiCh/eftexc+rzWr/7oDM7SiNb9x/SxY/P0p6DFXp93mb5PP5/BwCQGDluBwDAPT97bbGj+xvQpbWj+7NKzLA9P8PRGlWw75DbIXjOs59t0PJtRbry6dnauLdU5VU+fe/0/m6HBQBIMipPQAabvHyHo/vr3KaFo/tLWOUpTXMnp/s70DCivsLSSknSgbIqlyMBALiB5AmAY2Z/tS+h+48n51m4qVBfrN8ryfvDFWPx0apd2llU7ug+aRjRtMpqv259fbE2U60DgIzAsD0AjlmxvcjR/dVb5ymOc/lvPjVbklQwcYLSMHfSDS8tcDuEjBL6Ls7duE9vL9mufSWV+ucNo90NCgCQcFSeAHhW+Jwnp+w66GyFBpmDkYwAkNlIngB4Vr3KU5JblZsMb9nNnKeGbSk8pH63T9bK7cVuhwIASCKSJwCOcfpUO1Gj6+i2h3h9tHqXJOmthVtdjgQAkEwkTwA8K7wBRbXPOrK+Dmv0AACAWJA8AXCM06O8fhjWBOFrj8/SVc/MjmufFdW+qBtPfL5+r479/fs6WO5sW+rdxc7OudrNHC7X0JEQADILyROAlDK/YH9cr99VVBH1Ce/BimqVVvq0ZufBuI4Z7tMv9zi2r/dX7NSoB6c7tj80jlwJADIbyROAjJNOo/YWbY4vmXTbtFW79N6y7W6HEbVQdTWNvkIAgGZwNXkyxlxkjFlrjFlvjLk9wuPGGPNY8PFlxpgTaz32gjFmtzFmRXKjBpDqyqp8zXq+l6sNqT5/64cvLdDNry7W+t3OVvcShf6DAJDZXEuejDHZkv4maZykYyRdbYw5Juxp4yQNDv65UdJTtR57UdJFiY8UQKbz8ryW52dtdDsER7y7dIfbITRLeBI1a/1evTy7wIVIAADJ5GblaZSk9dbaDdbaSkmvS/pG2HO+IeklGzBHUgdjTE9JstZ+JqkwqREDaFQqrIuUqIV3kd7+MXtTnfuRvkV3v70yOcEAAFzjZvLUS9KWWve3Brc19zkAPCJd109Kz3eVPL/733L1u32y22GkhU/W7tbMdc41HAEANI+byVOkS9Th5yjRPKfxgxhzozFmgTFmwZ49/MIBEulQZfPmEmWqTEvG/jlnc5PPcbrNvVOWby3SUb+bWm+7W+Fe//f5uu75eS4dHQCQ4+Kxt0rqU+t+b0nhLZeieU6jrLXPSHpGkkaOHJlp5yxAUrVvmet2CBGt2l7sdgiOm7thnxZsSu1Oe6ng+VkbVFntr7kf/kuEXyoAkFncTJ7mSxpsjOkvaZukqyRdE/acdyTdbIx5XdJoSUXW2tSaVQxkkLwcb65+MP6xmTW3//HFpkaeGZnToxGf+Hi9rhzZp+knNuJbz8xxKJqGJbO6kgrz5aQIn0mSsqc3529Rpc/f9BMBAAnlWvJkra02xtws6QNJ2ZJesNauNMbcFHx8kqQpksZLWi/pkKTrQ683xrwm6RxJXYwxWyXdY619PrnvAkBtqXD6+8Lnze9O53STic2FhxzdX6Iks6ri1WF79caSBwOt2Z6kuG/797LkHAgA0Cg3K0+y1k5RIEGqvW1SrdtW0k8beO3ViY0OyDynT/xYZx3VVQ9fNsztUABPSNMeKACAGHlzjA0AV2w7UKbX5jU9ub8h5x7dzcFoPIQT6ITzaOGpaXw3ACCjkDwBcEyXNi3cDgEOStmEJoEKSysDN0JJEx8SAGQUkicAaeeDlTvdDgFpoqHC0sGK6ojbtx0oS1wwAADXkTwBSDs/enmh2yGgCdbaOgvnbi/yZtIxq4kFaTfsKa1z//q/swYTAKQzkicAjvHCCKbpq3c5v1MvvLE0E165eW3eFpciaViVz6/9h6qa9ZrissgVqVTj91v9edqX2nOwwu1QAMBTXO22BwBO+8E/FrgdAtKEP4ZWe063tXfLgk379dj0dXryk/Wq9lt98utz1L9La7fDAgDXUXkCAMAhu4orVFTWvGqVF1X7/cG/A8ngzHV7NHU5a9QDAMkTAAC1lFRU6/P1e7X9QHlMr//OC6k/78mEjVX9/dsr9eNXFmnFtiKXIgIAbyB5AiBJuuM/y+LeR3oMWEKm2br/UJ25cj9/fbG+/dxc/Xvh1pj2t2zrAadCc41pYJ5faQNdBr1mX0mFdhbFlvwCQGNIngBI8uaE/XT29pJtbofgqhimEyXM+Edn1pkr9+WuEklSWZUvpv156b3FqqEkyTSUVXnMSQ98pFMenu52GADSEMkTAMfM2bDPtWPPWrdXg+6c4trxm+vW15e4HYKrvHQOXlweOVGIJwlas7P48IK6KWZ3cTmNVwCgASRPABzz2ZeNr4mTSI99vK5mcju8ryRCwrKl8JALkRw27tGZjg1Lu+ivM3XRXz9zZF/JtqOR4W7VPr/2ltC+HEDmInkCgCaET55H/K7/+/x628585BMXIjls9Y5iLd58eL7SC59vjGt/u1N0jaTGLkH85q1lGvnAR/J59ELFmwu26JM1u90OA0AaY50nAI7x5ukU3GQbGPu2dtfBiNu/3HVQR3Vvm8iQGmVltdnlClht+0srPfX/atuBMkmSz2+VneXuRQVrrX73vxW6dEQvjezXSZJ021vxN74BgMZQeQIAROTEvKSlW5vX2vrCv7g71O26573VZnzE/dN04v3TknY8a21U61R5YTFgv5VembtZVzw92+1QAGQQkicAaSGR8zCenxXf8K1U5UTXuGqfP/6dIGn+OXezvhvFOlXp0FEQAGJB8gTAER+v2VVnvkgy7S+t1IY9pQnb/0erd2V8a3Ek36cuNGD5dG1084W8kDw1NCQUABKJ5AmAI77/ojutja21GpGEYU2Z3lo8Vpzexi6aCpBb/B5KXDwUCoAMQPIEAIjIK2sxbSk8pF+8sUSV1QwB9AovJE/uRwAgE5E8AQA87Y7/LNd/F2/TbBcXYUZdt721TMPu+aDOtl3F5UldA8oD+RuADETyBCBl/fGDtep/xxS3w0hb8Z6cHjhUGefxrWZ/tU+z1u+VJC0sKIwvoBQwedkOrdlZ7HYYTZq6YqcOhi0oPPqh6Rr5wEdJi8ELHf8AZB6SJwApqaLapyc+We92GGjEpU9+UScBi3Zh1T3BxWX/tXCrrn52Ts32L75K/8rTT19dpIv+OrPJ5+0rqdDqHc4kWQsKCnWwvOn25AAAkicAKWri1DVuh5D24p3ztHFv3Q6Ip02cHtXrvv1cIGHatr+sznYf47RqXPbUFxr3aNNJVlOKy6t0+aTZ+skri4JbmveP/v6KnXpz/hb9/u0VccfSXLW/DlsKD9Us4AsAiZTjdgAAEIuCvYlrTY7E2FUc3XyYgn2HtOdghXKz657IR1m4ygib9h1yZD8VVYEmHKu2x1bFuumfC+ttW7hpv9q3zNWgbm3iiq05znzkk6QdC0Bmo/IEICWlw3n015+Y5XYICRfLWjyV1X6d/OBH+sfsTXW2+8me6nFqraNQlXHW+vjXlvrmU1/o/D9/Gvd+GvPI+2v00epdCT0GAERC5QlAg8oqfdq4t1THHNHO7VDq+MYTs1Tg0JV3Ny3bWqT5BYU6uV8nt0PxpNDcpxAvtMf2GmvjG14Z3nShvCo12sE/OeMrt0MAkKGoPAFo0M/fWKzxj81Usccmky/dWqSiMm/FFKvSsI5ljZmyfIdeml2QsFi8rqisSgsyoOOeJE1dviOq5+0pqdCHK3fGfqCa3Mkji3o14ZtPfcF8RwCuInkC0KCFm/ZLOjwvAu76ySuL9Pu3V7odhmu27i/T5ZNmq6QZCWeq+nFNA4fGfef5ebrx5YU6VBnfZ+KVBZEbUlJRrcpqvxZu2q9Jn1J1AuAehu0BiGjzvkPaWxLfOj1omonhrDVZV95/89YyFZZWqmDihJj3kYiBdpXVfqmFM/tK9XlUBfsCjVOqfLG9j9CrwodIes1x93ygk47s6HYYAEDlCUBkZ/0f3avC7S1x/gTz9n8v098/39is1yTrynthqTeT52jXi4rGvxZucWxfbsgKJt+xNo6o/TKnmk84qcrnr0lwQ5VwAHATyRMARGnkAx+pvMrn6D53FJXr3ndXObrPdOfkSb7XKy5NCRUuY80nazeMWL6tyIGIDhtx34f6+euLY3rtlZNm6+lPv9Lgu6bq528scTQuAIgHyROAJpVX+TzXNMItFdXM/2qORBQzdjeQ8Fhr9cma3c1KrmIZNtkcn6zZrY/XJK6ldij6WDsR1n5ZZbVf/bu0jj+ooP2HqvS/Jdub9Zpjfv++/vbJes0rKNTDweGp7yxt3j4AIJFIngA06aK/fqbj//Ch22F4g/dGNmWcldsjV0j+u3ibrn9xvv45d3OSI2rY9S/O1/dfXJDw48ScPIXdv+SEXvEHE4XJy3bUWZj39Ikf608frtWhSp/+74O1jh2nrNKntTsPOrY/ACB5AtCk0kpnh6qlMjfWGnpu5gZd8rfPk37cRLk1xqFcIQ0NUdtRVC5J2rS3VF9/YpZ2F5fHdZxUYOvdaObrw77Pyeq699NXF2n8YzNr7m87UKbHP17v+HFufX2xxv71s2YtCQAAjSF5AlBPtY+haQ1xo/D0wOTVWrLlgAtHdp7fb/V2M4dyhdtxoKzeNmutnpu5QZL03KyNWra1SKMemt7ofjbuLdWj09fFFYtXxDrn6WB53aQiGblTv9sn19we88cZeuazxDVAmRdcF6yS4bYAHELyBKCeX/9rqdsheJYXO5J5mQ1LN8ur469iPhZWoXh93mb1v2OK9h9q3ry8656fm/In1aGvoxNznoyRsrKcT58ue/LzBtvrb9xbqoemsOgtgNRB8gSgnmmrIk9wr6IiFfMVfjhr2dbDlbi/zYhtuFc6NP8IJadOfC0TdV1g0eYDNe31i5qZ4MbrUHDIMf9tATiF5AlA1B55P3CFuKLal/JX7GMVXklJpBv+MV//W7wtacdLBqdO0L/+xOdas7NYv3hjiUorIlezzhzcRVU+f4PVwlRvUy4dTuZjXew3/Puc6DlPw+9LbuOZ0M8pKsYAnELyBKCehhpErN4R6Fo19O73NfKBackMyTsSeA62df8hnfLQdG0pPCRJ+mj17tRf4yaBn9dFf52p/y7eprb5OREfL6mo1uC7puqJBDQi8Iw4P9/wnGL2V/vi22EjalcLky3RLekBZA6SJwBRqxkiZKXi8szsXpXI69dvLdyqncXl+teCLQk9iU03DRUVCksrJUlvLtySxGjc4UQXyMpqv2au2+tANJF9/QlvdYys8vkdX/QaQPojeQKAZgido+4rqdCEx2bWVImcYIK9zrYdKNfVz85xbL9uuu3fyxJ+jIaGUtYsIJvGI0xD7z3WuXi1c65rnpvrQESp48qnZ2vo3e+7HQaAFEPyBCBqSzanR7vseJzy8HSt2l6st5ds18rtxXp+1kbH9h1qdFZSkdxJ9Ym0dX/9tuJOayg5KtgXSGzTeb5L6K3F+h6TOYfPTZE+n8X8PAMQg8gDxQEggtJKnw5VZuZwvdpmb0jMkLrQtIw0Ptd3xfaicm3ed0h9O7dyOxRJgW6Wndvk6cS+HePeV+irQhfIxvlq/af6y7QvMyRlBJAIJE8AmuWY339Qc/uLr/bqtIFdXIzGHT6/X1nBTKe43Jkq0e7i8ppJ7SUVJKjNEc18n+//Y75OHdBZN5zZX0d2bp2EqBr2w5cWSJIKJk6Ie1+HKyrxr/OU1mq9z3RZGBmAOxi2ByBmiZxc7mVGRgs37Zck/WeRM63Ef/zKoprK0xdp3CwiEd+ZaBKA9btL9PKcTbrl9RTvXhgm3spTBuZOABAXkicAaCZjnKs4hRwsr6ppGJHOGlqAOR6xzttp3zLX4UiSL5Q4Rqq+vb1kmx6nyiLJmW6EACCRPAGIw67iclVUZ2ar3+Vbixzdn7WJX6A0HpXVfj02fZ0nWzs3p+qSVeszTqcT6khv5dbXl+hP075s4nXp8xk0hjlhAJxC8gQgZv9ZtE0/fWWx22EkXZYxys129sdnRbVfE6eucXSfTnppdoH+PO1LPTdzQ1z7SUR3t1RIAGat26vP1ydumKuP7KBRfj4fAA6hYQSAuAXqgVwAACAASURBVHy02vlhWF6XZaSsLGfLRAcOVTq6P6eFKk5l8VaeEnAO25zcqfa/WjJzrmufD6yh5ESTiKY8OHmVWubx6x0AEoHKEwA0kzFGV4/qK0k6Y5Az3QaLy1Ojw168CUci3ue+0ugTz0W11vZJp66Gtf9dnp25UY8x16mOsiqf7v7fCs9fpADgfVyaAoBmMkbq3aGlJKlH+3yXo0ktmVipbMju4nJZSd3bxf8damz+VklFtdbsKNbIfp3qPZYpg9n+vWirXp6zKeLnZK2tWSYAAJpC8gQAzWSUWQvarthWpD9+GGg8kE7nmO3yc1yt+I16aLqkwFC+J2esV484kqjGvobH3RNYm23lvWPVukVm/tr3+QKfUKS5YT6/VU52Gn2xASQUw/YAoJmMMTVXqhtqgLBs64G0maRee22m8GTxtreW6qi7piY5Ime48a8zv6Aw4vZH3l+rX765NOb9RtM5sKLaH/P+00Wkj6m0wqd5GyP/uwBAOJInAHF7eXaB2yEkVZ3ubhFOxuZu2KevP/G5npsVX2c6rwivNhWWVtbMF3pzwVZV+vz6ak+JC5HF56yjuib9mFdMmp2Q/Ya+k+8t217vsVBvk0hVl1ToVOikSBc7bnl9sa58erY27i11ISIAqYbkCUDc7n57pdshJFWL3Oyarm0zvtyjfrdP1o6iMkmBIW7femaOJOm5mRtdijBxnpzxlU68f5rG/HFGne37m9G0wW3zCwq1btdB9e/c2u1QHBPKgW5+tf7SAW3zA4sBV/szt/IUSpkKI3xPP/1yjySpJEWatgBwF8kTAMQgVI0JnYwtCXZxm7F2d81zBndvk/S4kmXPwYo691OlftGxVa6umDRbF/zls7RaJLexEaKh4aP7S6u0antxncfS6CNoVOj/5Uerdzf4nHSazwcgcUieAMAB1cET1Crf4bPRDi3zUnI4Wzrr0Cqv5vaTM75yMRJnzd2wTw+8tyriY6Ek8TsvzNX4x2bWGaqXJtPymvTVHobkAXBGk8mTMaaVMeZuY8yzwfuDjTFfS3xoAOBNizfvrze5/2evLVZ5lU+b9h0+SZu8fIfO+9On9a72p5qJU9e4HYJj0rW48KdpX+q5WZGHifqCydLekkCVtLwqc4fvNeaLr/bquuBixgDQkGh6lv5d0kJJpwbvb5X0L0nvJSooAPCyz9fvi7h9/e4S/W9J/Qn78zZGfn46SZXhX14cmlVe5Uvo/sOnOlVW+9UyL1tS5jWMaMxDUwIXCcqrfMrPzXY5GgBeFc2wvYHW2kckVUmStbZM6XvxDgCatLnwUMTtk5fviLj9iU/SZ3hYqvPiYqilFYltVOALS5AqfYezKVKn+qp8VOYANCya5KnSGNNSwZ+xxpiBkioafwkAZJ5IraAlaW9JZvzIvO/dyHNuvMSL/xa158klQvj3sk7yRPZUT3WC/z0ApLZokqd7JL0vqY8x5hVJ0yXdltCoACAFvblgi9shuOqFz73fmv3AoSq3Q6hn+ppdST3eok37a24zbK++qgxu6Q6gaU0mT9baaZIuk/Q9Sa9JGmmtnZHYsAAg9XjxxDyRai/ImgnzuhLlrv+uSOrxfvba4bWgSJ3q27a/rM6SAyHzCwp12sPTG6wwA8gMDTaMMMacGLYpNJi/rzGmr7V2UeLCAgB4Xe0FWZ9NwwWBkZkuffILSdKbPzpVo/p3qtl+xaTZkqR5Gwt16sDOrsQGwH2NVZ7+FPzzN0lzJT0j6dng7ccSHxoAIFUUlWVW1S3VPTljvfrdPjnjqqXN8YMX56va51dFdd1uiMZI1T6/1u066FJkANzUYPJkrR1jrR0jaZOkE621I621J0kaIWl9sgIEAADOeuT9tZKkKQ10iIRU4fNr0F1TNeR372v7gbKa7XM3FGrQXVN1wV8+q7OuG4DMEE3DiKHW2uWhO9baFZJOSFxIAGJRsLdUew56r5MYAO+avYG5ag2prD7cOOK0iR/X3P7LR1/W3C4sray5XV7lU8HeUlX5/NrSwHIGtVlradgBpKBoFsldbYx5TtI/FZhbeq2k1U4c3BhzkaRHJWVLes5aOzHscRN8fLykQ5K+F5pr1dRrEZ3Kar9mb9ins4/qWmf7aQ9P1/aici2++wJ1bJ3nUnRojnP+OEOSVDBxQqPPW7ipUEu2FOkHZ/RPQlQAvKz2yT+aLzQ/atV9Y3XM7z+o89i7N5+hvp1aqX2rXBWXV6ltixwZY7SgoFAvflGg95YFqn7rHxynnOxormUD8IJokqfrJf1Y0q3B+59JeireAxtjshWYT3WBpK2S5htj3rHW1l4oZJykwcE/o4PHHR3laz3PH+zYk5VVf9FGa23NYo79bp9cs/3Rq07Qra8vqbl/5cjemnjZ8TJGGn7vhyour9biuy/QiPunSVJN8lN7H//9yWka0bejKqv9Oup3U2u2h066f/76Ym0vKpckjbh/Wp2Tcb/f6upn52juxkJJ0lcPjVd2lpG1Vv3vmFJvX1JgjRGf3yovx9u/HHYUlSkvO0ud27So2eb3W63eWayV24o19rgeat8yt957laR2+Tn64o7z9PzMjXWuSoY+n30lFXX2m0h+v434nQr55lOBSc8ThvVMSjwAkO7CEydJuviJWfW2dW6dp31hCeuguw7/Hh7QtbUuOLq7bh83VFJgUefC0kpVVvvVvmWu7nlnhd5csFUbHx6vrfvL9MDkVRp5ZCf98KwBjcZX5fNrw55S9erYUldMmq0rR/bWd0/tp6zg7+8Dh6qadaG0tKJaudlZUf9er31OU9u+kgp1bJXX6O+sRKh9TtTUBceG3Pnf5Tp9YBdNOL75v0v9fitjYlu02++3WrWjWL07tlS7/NyEfHblVT7tKCpX/y6t62w/WF6li/46U9uCw1jvHD9ULXOzdffbK2ue887Np+v43h0cj8lLjFslY2PMqZL+YK0dG7x/hyRZax+u9ZynJc2w1r4WvL9W0jmS+jX12khGjhxpFyxY4Ph7aa4XZm3Ufe+5m+c9cc2IOp2yJOmpb5+oscf20IA76yYGbVvkKD8vu8EhYb8ZO0T/98HaOtvGDOmqG84coG8/N7fO9jX3X6QnZ3ylx6avq7P9i9vPVeu8HA2/78M6288/upuuO7WfvvvCvJptd40/Wj88a4AmTl2jorIqvTZvc72Y/nzlcP3yzaWSpPd/fqYGdGmjgn2luvAvn0V8D16x+O4L1L5lrrbuL9Nbi7bqF+cPbvKH65TlO/STV2h+CQCI39+vP1nrdh3UuON66sxHPqnZ/tlvxuiCv3yqiuq662B99Muzdf6fP623n5X3jtU1z87R0q1FccXz5o9O1XXPz1VFtV9t83N0sLw64vO6tGmhvSUV2vjweBljtKu4XKMfmh54T987WWOGdpNUN3EKqZ1ARXpckjq1zlNhaaVuOW9wvXOYkOe+M1I3vBT7eWaPdvnaWVwe8+vjNaR7W61NcCOUi4cfoXeXbq+33WsVWGPMQmvtyIiPNZU8GWM2KsJSENbaxi9zNB3U5ZIustbeELx/naTR1tqbaz3nPUkTrbWzgvenS/qtAslTo6+ttY8bJd0oSX379j1p06ZN8YTtiJXbizThsfpXpLxmdP9ONRUmAACAdDSqXye9edOpOvORj7WlsKzpFyAhvnHCEXr0qhFuhyGp8eQpmmF7tV+YL+kKSZ0aeG6z4oqwLTxJa+g50bw2sNHaZxRos66RI0d6YmbmsUe0r7nKUV7l0x8/WKszj+qqtTuL9a2RffXx2l06Y1BX5WYbdWgVXRm9stqv7Cyj7LDy7a7icvn8Vt3b5Ss7y6is0qejf/9+zeNnHdVVL31/VL0rLdN/dbYGdm1Tb/sz152kC4/tIUkqLq/S8X84XCl6/+dnamiPdhH3VVnt17hHZ9bZHmn4Qix6ts/XjqK6V2qm3npmveM1ZvywHrr2lCNlrfTt5+aqT6eW2lJYphP6dNArN4xWbnaWLnvqcw3o0kZrdx7UGz86pc6/jbVWVT6rnCxTU0IvKqvStFW79PKcTXr2Oyfp3aU7tHJ7kT5cuUslFZGvnAEA0tu3RvbRGwu26K7xR8tvrR6eukZS4Kp/dpbRqh3FUe/r5jGDtHpHsaavqb+obyTnH91Nvx47RGt3HtSv/7VUVT6rb57YWyf0aV9n6FVTfjfhaHVqnVczwqMp3zn1SE1fvbtmuJcUqEB899Qj9aOXF+rn5w+uc/xHLj9eCwoK9eaCrfX2dcu5g/TqvC3aW3J4NMyZg7to5rq9Ucf/7dF99eClw2rOV+YVFNY7dxl3XA9NXbGz3mtvOKO/npu1UR//6mz5rWqqbvd+/Vgd1b2trn52jiYM66lxw3rog5W71K9zKz3+8eEm1W1b5GjWb89VqxbZmrZql6yVxh7bXQ9MXq3LT+qtl2dv0hsLtkiSBndro3W7S6J+X81ljPTQpcO0cNN+Ldq0X7ddNESfrNmjc4Z01bhhPfXJmt16cMpqbdtfpvu+caxG9O2gQd3aNrpPv99q4eb9emz6On3vtH7aur9M97wT3Xdrd3FqNL2KadieMWaWtfaMuA6cwcP2vGDl9iLlZGVpSI/Af4I9Byt08oMf1TweSu5C83v++YPROmNwl6j3P2Ptbvmt1blDu9fZvmJbkXp1aFlvbLW1ViUV1Wqbn1tne0W1TyXl1XXmC5VX+fThql06fWDnqOcR7SouV9c2LZI+rjoWB8ur1DY/t6Zj07l/qj8cojH/75vDNLRHOw3s1kb7SipUVuVTv86ttau4XBv2lOr43u3VoVWeBoYNzwQANN8VJ/XWvxZu1QXHdNe0VbvqPT7vzvOUk52lTq3zVFntrzdP6MXPN+qSEb3qXSz1+a0+WLlT5w7tpvzc7DqPrd15UH06tVSrvGiugTdPv9sn66qT+2jssT10ZOdWGtC1jf61YIt+89YyvXrDaJ02qO65QHF5ldrk5dT5/Trp0680ceoazbxtjPp0ahVXPLuLy9W5TYt6F4cjKa/yaejdgQvEC353vtq3zFVudpZOun+a9pVWqleHlpr+q7PrfJ5NDePzkkWb9+uo7m21ePN+De7WVqc8HBiW2CovWzN+fY66tm2hL3eVqFfHlvL5rFrkZikvOyslzn28Jt5heyfWupulQCXqx9ba4XEGlSPpS0nnSdomab6ka6y1K2s9Z4KkmxXotjda0mPW2lHRvDYSkqfGHSyv0vKtRfV+MMLbQhNxQ78AmvNDv6Gx3XDWzNvG1Jk7AHhBXk5WnXbciM3Gh8dr98EKdW+XL7/fasjdU3XPxcfqjflb9JNzBmoczXk87cChSp1w37Sa+16bewN3xDts70+1bldL2ijpyniDstZWG2NulvSBAu3GX7DWrjTG3BR8fJKkKQokTusVaFV+fWOvjTemTNc2P5fEKQXF0q0HyRXvlVc4KzQsN9N1aJmr3awNFzdjjLq3y5cU6J677sHxkqRrTznSzbAQpQ6t8jxbaYI3RZM8/cBau6H2BmOMIwvEWGunKJAg1d42qdZtK+mn0b4WyGQf/+rshAzhANJNngevKrfOy1ZppS/hx8nPzVJ5VaDaNH5YT734RUHCj5nqzj+6mz5aHZhTNLRHW63Zebgb2eK7L3ArLAAuieZM6y1JJ0bYdpLz4QCI1YCubdwOAUgJeTnZTT8pyfJzk5M8ZdeqVHdiAfSoPPfdk1Wwt1Qfr9mty07sVWeIF4vIA5mnweTJGDNU0rGS2htjLqv1UDsFuu4BAJBy8rK9N9Q1vCFAovRon6+v9pRKkm48a4C2HyjT6/O3JOXYqSTUWCBUpezXpbW+f0Zg0M3Gh8drfsF+FewrdTNEAC5pbOzCEElfk9RB0sW1/pwo6YeJDw0AAOdF07Ur2VrkJGcoYU5W4Dg92+crPzdbPzlnUFKOmyoevzqwxszpgzorPzc7YpcyY4xG9e+kK0f2SXZ4ADygwcqTtfZtSW8bY0611s5OYkwAACTMos0H3A6hHicSugFdW2vDnqarIZNvOaOmwQHqunj4EeratoWG9+7gdigAPKqxYXu3WWsfkXSNMebq8MettbckNDIAADKEE8lTNHswJrBQOxp2yoDObocAwMMaGyewOvj3AkkLI/wBAAAOcCR5CjaDuPCY7vUeu3kMw/MAwAmNDdt7N/j3P5IXDgCkthX3jtVx93zgdhhIMVnBxCcvO0uVvtgWrg3lX7lhrdiP69VOY4Z20xOfrK/TZluSrGxMxwKATNXYsL13pYZ/qlprv56QiAAghbVpkblrbS37w4U6/g8fuh2GZw3r1V7LtxXV2Ta8d3st3Voknz/w6zY/N/bkyQQH7uWEdRPMzsrSwfKqiK+x5E41Lh3Ry+0QAKSAxn7L/zFpUQAAUs7RPdtpzJCuenLGV5Kkdvm5LkfkbXlhHfV+cEZ/7Swur5M8xZPMhJZwCnXUC7HW6pQBnZWXnaVHrzoh9gOksdH9O+lPVwx3OwwAKaCxYXufhm4bY/IkDVWgErXWWluZhNgAAB715o9O1cgjOyory9QkT2hc+LSm52dt1C3nDZYktW8VSDxLKqvjPk5uhHWs8nOz9eWD4+Ledyob3K2N1u0uifjYpGtPitiWHADCNTm+xBgzQdIkSV8p0MynvzHmR9baqYkODgBS2aRrT4p4IpvqurZtoVH9O7kdRsoJNXSo7ZZzB2l47/Zatb1Y8zYWxlV5Cs2bCm8+8dZNp8W+0zRhzOHKXCQdW+clLxgAKS2awfl/kjTGWrtekowxAyVNlkTyBCAjnTKgk+ZsKKy3/ZrRfevcP//obsrJTs7ip/C+SOfuOdlZOu/o7lq1vTj+/QcPkBWWJYQPF6wtk6Y8fbkrctUJAJojmt/qu0OJU9AGSbsTFA8AeN4/fzC63raCiRP00KXD6mxzov20F/3sXNpexyKU01w9KpBk/++np9c85kQSczh5OrytMxUVSQ2vgfXQpcO06r6xSY0FQGqLpvK00hgzRdKbCvx8v0LSfGPMZZJkrf1PAuMDAM8JryadM6Rrnftt83N0sLw64jCtVFcwcYLbIaSsUDe8c4Z01cOX1U20Z63fG/f+QxWn2t+7d392Rtz7TQf+BrLT8GoxADQlmspTvqRdks6WdI6kPZI6SbpY0tcSFhkApICCiRP04vWj6mybf9f5mn/X+VHv452bT2/6SUhJN5zRv+Z2ebVPUuQqiBMVosPJU+D+hON76ogOLePeb7oY3K2NpMMXO34zdoib4QBIUU1Wnqy11ycjEABIJUt/f6Gq/ZHX48nPzVZ+bnbU+xrQtY1TYbmmFyfpEc0vODw3bvHmA5KkZVuLdOGxPeo8b1jv9pq6YmfMxxl3XA/tPlghSTVtz6Ope9oMWuipJrkM3k/DwjCAJIim215/ST+T1K/281kkF0AmC7WWdkKqL6y7/A8XKpfGGBEt3VpUb1ukk/bQkL52+TkqLj/crjwny6i6oTFnQWsfuEg5WVm6+pk5klTz/GiGjXo1dTLG+QV8Qx+Hz6tvGkBKiOY39v8kPS/pXUmxLXsOAEhbbVkct1laROh+F2ryEO15/RHt87W9qDy4v0CVM7Q2biZVk5ojtIhz6LM2UdXmAKCuaJKncmvtYwmPBACANPbjcwbqqRlfRawkhRLQ1nmBZiNN6d2pVU3yFBIalladBqUVo7qJZKgJSyzycrL06wuP0iUn9NK/F23TgUOVmrF2jyNxAsg80SRPjxpj7pH0oaSK0EZr7aKERQXA80b166R5BfXXOkLz3HjWALdDiMrnt5+r7m1buB1GXO7/xrG6++2Vrh0/P1gh8kdInq4c2VslFVVqmZsdVYyRuuCHWuOXVQUaU2zbfyiOaN2VZYz8tSpo8dSIvnxgXM3tH58zUB+uDMwtG9arfRx7BZCpokmehkm6TtK5OjxszwbvA8hUJrDeUeGhSt3y2mK3o0lZd44/2u0QopIODSG6t8vXH68YrqE92uprj89K2nG/d1o/LdlyQKFpYb4Iw+pysrN041kD9eb8LXW2N1RDCl8IV5KuHNlHM9ftVd9OrSQ13J47FSSymcOFx/bQvLvOU7e2+Yk7CIC0FU3ydKmkAdbaykQHAyC1nDG4iySRPCElZBmjy0/qnfTj/uHrx0qSdh8s1wcrd+naU46M+rUNzV+KlDxdPPwIXTz8CL00u0BSelVWnM4DSZwAxCqa5GmppA6Sdic4FgAphKnWmeOCY7rH/NpeHVpq24EyB6NpviwTqMK43Zq6W9v8phetDYvRNNB2rrH38s0Te2t+wX7dev7gJmPyam+JQKdAjwYHIKNF01u2u6Q1xpgPjDHvBP+8nejAAHib2yeiSJ5vjewT82un3HJmnftv3XSqTh3QOd6QmiU0FyhStcZrwiNsqPLUWBvy1i1y9PjVI9SlTTRz1EhQAKA5okme7lFg6N5Dkv4saZ6kQYkMCoD30eY38b49uq/bIUiSzo+j8tS+Va7GDzu8IOzIfp303dOiH7bmhFCiUTvfGNi1dVJjcFqkhhFphZwOgEc1mTxZaz+VVCRpgqQXJZ0naVJiwwLgdSlwET/ldWqd53YIjggvniS7kUEo0ahdeZpy65ladd/Y5AYShfCKUkMfFf/96kqHhiYAUkODc56MMUdJukrS1ZL2SXpDkrHWjklSbAA8jOQp8QakeHWkIcmumpRXBRrF1v7OhhaW9ZpoP5rGhu2lAxueNjaRcGdFM44GABzQ2I+bNQpUmS621p5hrX1cki85YQHwijvHD9WMX5+j1nmBk83QFV6G7SXW147vqUtO6OV2GI4IrzyN7NfJnUBSQHiO0FBDh7JKZ34de7VhRL24wn7ctMvPCXuYn0cAkqOx5OmbknZK+sQY86wx5jwxUgDIODeeNVD9urTW0T3bSZIuOzFwQp/mF75d98Q1J6ZtdSHHpQk77y7dnvRjNvetLtmyP6rntchN71JLvZwubENxeXXYw4EnpOl/GQAe0uBPX2vtf62135I0VNIMSb+Q1N0Y85Qx5sIkxQcggbq2jaYbV4BHL1AjBfxkzMA6992qEnz25d6kH7NPcMHaaPWN8vk92wcqwGOPjb2ZRzrZUhhohx9esRp3XI8IzwaA2EXTMKLUWvuKtfZrknpLWiLp9oRHBiDh8rKbf/V6VP9OGtWvk3434ZgERBS9lfeO1Yl9O7gaAxoXmrN1fG9v/Du5UZW4Y9zQZj2/ZW70c7EKJk7Q09eNbG5IdaT7RREqUQCc1qwzJ2ttobX2aWvtuYkKCEDyNLSGTGNa5mbrzZtO1ZAebWu2tWkRzXrbzmrdIkf5tU40Z/2WXjZe8/GvznE7hDquPSW5LdIlKaeZnQy+2lOaoEhSi7+Jn01d2gQ6UeZmN54dxXKBCAAak/wzHgCe4dRV55wmTmASZf+hqsMx0G4LTejQKjfpx2zu/7Fjj2iXoD03sJcULT2VVgQaZgSGgEZ+EzedPVA/OmtAEqMCkAk42wAyWHNOnCYM6ylJ6t2x/pwMt0bG7CouPxwDw3NSh0v/Vke4sBZQtc/frOdH/18yvb/wTXXbK6vyRdwecvqgzrp93FB1TJO10gB4B8kTkMFOH9Ql6udef3o/rb7vIvVon5/AiJrnshHp0cobiTXlljP10zEDNWZIt6Qfe+qKnc16/pgh3dS+Za5+cEb/Rp+XiIsF3xrZR+/efIaj+2zr1JDeBrLKhj6Grm2ib4YDAM1B8gRksEcuPz7q5xpj1DIv8mR2t1pqp+iIo5i897MztOB357sdRkrq1DpPvxkbuXFDohci9vmb9y3t2raFlt5zoQZ3a5OgiBrWMi9bw3q3T/pxo9HUpxg+9ymbYbwAEoSfLkAGy3ZpvR2n1J5U7tbaQfE4/+jDbaYba7rRu2NLHdervbqkydX0ZOfabg7pHFqrsUpz7CutbPTxVPm2H6yobvpJUWjo/Yb+bUPt7zsFh+nl5aTKJwQg1dAwAkDc3DpN8de6qt85CYnFqQM66/5LjnNsf89cd1LN7Y9+ebZW7SjS919cUKdD2Ge/GaP2LjQ6SKSsJGUzxgTmzjR6tASXL68Z3Tem18XSCTNeiThmi5wsVVQ3b95XLEKL5FYFj0UDGQCJwk8XAJKkp2udyDeXW1f2vzb8CEkOzqtowms3nqJBDg6nyqpVLevRPl/nDu2udQ+O08r7xtZs79u5ldq3TK/kKVmt7bMOlyUa1DY/cbEUTJwQc1LfVJ8Jp/7PDUzgsMU5d5ynV394iiP7aiqtC+V91cELKm51AAWQ/kieAEiSxh7bw+0Qmi104tuzg3eaWMQrNztLuR5am6Zf5/rdFVNFVtiQrkievm6k7hzfvIVsk6GpdY6aOZWqQTnZWfrDxYlZ8LpH+3wdGfz+jOrXKSHHKK8KZJmhz+tbJ/fRRcf20E/HDErI8QDAO7+hAbiid8eWuunsgXHto12+O5WRxk6K4Yxjol53yHtCjUwamw7Xo32+bjwrvu9/IjSVG706d3PSjxmLLm1aaMND43XdqYldoPiCYwLzBy8/qbcmXXdS2swPBOA9JE9Ahpv123N1+7i6V97XPThOUmCOTzQeuNS5eUCxSNWFPlNBsuYnJUJN5SkF30My5zwl+vPJSkIzlyHd26pg4gQd18ub3QIBpA8aRgCoJzc7SwUTJ0T9/NMGdtGGh8ZrwJ1TEhhVfb07BhY9vflchugkSiomHiGhxC8V38GcDfuSdqxkJGrxHqGkia59XD8BkCwkTwAckYyry5J0Qp8ONe2fW7fIaVaSh+ZrlRt5ba9UUJM8pWD2NLp/Z80v2O92GDEL/8xDc+cGdWuj9btLHD8e1WcAycKwPQAp5baxQzTxm9Ev7ov43PW1o90OIWbhawClkvA12PLCmoi0dDCpTUR18diwuXLH9+6gT39zjr4bnPt0cr+OkqSTjuzoyPF2FZc7sh8AaArJE4CUwgXm5HKrGYgTQimBTcNvzbdjXD8qWSK1Wj+yc+uaq0doxQAAHElJREFUjPao4BylEX06OHK8fy3c6sh+AKApJE8AUkpTLZzhTRcPP0LjhyW3HX6oopLIr0zXtknq6hZWHCour3L8EE5+Tv4GeqkfH2zocMagLnHt//je7VUwcYL6d0ncOlUAEAlzngCkFHKn1PT41SPcDiEhshM0oaqpr/nHa/Y4dqxEvIVqf+RVfof36aDlf7hQbYMVTV+M/6GrfPwgAOAOKk8AUgqnTIhWqBtjspqZJNPoAc4vOuvE8EZjpDYtcnTbRQ0vPNy21lDQ8NwpJyu6Jh/VwXGBG/eWxhYoAMSI5AlASknm+jeI3aNXneB2CHrx+lF64poRat8y9eZthecOldV1KzlOzkVzMrVsmZutFfeO1dhjoxuiecmIXpKk0wYG1pRraF2xXh1a6hfnH1Vz3xccFsiwPQDJRvIEIKWQO6WGb5zQy+0Q1LVtC33t+CMSeoxEtUFv3aKpbnru/0c4/+huunN8wxWmaJzQp4MKJk4INJOQGszkjjminW49f3DN/argsMDwroQAkGjMeQKQUtKxc1pz5GVnqTJSK7MMNKhbG/Vol69Z6/e6HYrjmmrh3cCUorg098LEc989WZLUt1Mr9erQShc/MSvuGEytv2uHc97QbnWeVx2c80TuBCDZqDwBSCmJOGlMJbPvOFczbxvjdhie8NEvz9Y/bxjtagyJqoQ2td83Fmxx7mBxls8uOq6nBnYLVI5iX3/KRgwlLydwmtIyL7Df0f0Dc73GBJOpnCxOYwAkF5UnACmlse5c5w7tpo/X7E5iNMnXuU0LdXY7CNRIVCW0Z4eWCdlvorTKy9Ht44bqgmO6x/T6Lm0CLd87tMzTzqrymk/11vMGq0OrXF0cHH55XK/2mruxUAOCc53GHddDq3YU66qT+8T9HgAgGlyyAZBSqhtpUcwInsxxdM92bocg6XCFqF/nVo7ut1eHllr6+wsd3WfDx8qXFH/zhZvOHqiBXdvE9NqfnTtY/3f58Ro/rGedWPp3aa1vjz6ypmNiqBIV+txzg/fbpWBTEACpicoTgJTS0PoxkvTLC49Swb5SfbWH9sXpbMW9Y5Wb7Y1UObQWbKhxwakDOmv2hn0xV2Bqa98qV93attDugxVx76sx5w7trtdvPEWj+kXX/vyBS45Tp9Z5jsaQl5OlK0b20QPvrZIkXXVyH43o21Ejw+Z+/eScgSqtqNa1pxwp6fAFE7pwAkgWkicAKaWxytOxR7TX9F+do363T05iROmrYOIEt0Oo4+UfjFK7/Fy1aeG9X12hhH1eQaEk56qgQ3q0jZg8De3R1qEjBJwyIPrBoKHEJRG+fcqRenvpdl08/Aj1bF9/6GLb/Fzd943jau6HGmucOpDBrACSw3u/gQC45tUbRqtXR2/PtWis8oT0dubgrm6HEEHdZD60/tBR3Z1JbvxhFZXTBnbWvI2F+qsH1tFKhP5dWmv+XedH/fyR/Tppxb1jPZlQA0hP/LQBUOO0QV3cDqFJdOlGuBevP1nZWUbXPT8v6cf2hxVCu7RpoaeuPVEj+nRwZP/5OXW71/Xp2Eqv/vAUR/adLkicACQTDSMApBQflSeEOWdIN9eqUpHm2pzcr5Nysp359Ro+RI7O3ADgLn4MA0gpVY3MeQKSLdHfxnOGdNVDlw7TXeOPliSZONdkisVL3x+lybeckfTjAoAXUesGkFKY8wQvqV94cjadMsbomtF9NXnZDklSz3b5ju4/GmcdFajqPXHNCB2q9CX9+ADgJSRPAFJKdfgkEyDo2lP6amdRuQZ2a6P3lu5IyDGMqZswhQ/bS9TXc/ywHnr86hEad1yPxBwgCl8LLlQLAJmM5AlASvExbM/THrp0mIrKqlw59gOXDKu5fce4oxNyDKO6taVQ7tQ2P0cHy6t109kDEnNcY3TxcJIXAHAbyROAlFJF5cnTrhnd1+0QEsqElZ5CrcTbtAgkTx1aOrt4LADAW0ieAKSUKnqVZ5xFd19Qb70jt4S3awjl8juKyiVJW/YfSm5AAICkcqXbnjGmkzFmmjFmXfDvjg087yJjzFpjzHpjzO21tl9hjFlpjPEbY0YmL3IAbvNReco4nVrnqUubFm6HISkw5ymSE/sG1nU6waH1ndx0Rgqs9wYAbnGr8nS7pOnW2onBpOh2Sb+t/QRjTLakv0m6QNJWSfONMe9Ya1dJWiHpMklPJzdsAG7LyUp+q+ZEGNarvdsheFafTi21q6hC0355lvaWVLodTh0mbNaTL1gR+9l5g2Wt1Zgh3VyKzDnPf2+kyip9OuG+aW6HAgCe41by9A1J5wRv/0PSDIUlT5JGSVpvrd0gScaY14OvW2WtXR3cloxYAXjIeUd3dzsER/zzhtFuh+BZXx9+hH4zdqgk6cjOrV2OJkzYrx1/sBKabYzOSoPESZJa5GSrRU6222EAgCe5tUhud2vtDkkK/h3pN04vSVtq3d8a3AYgg6XLNZP2LXPdDsGzvDytLfzr16EVDSIAIJMkrPJkjPlIUqQFKe6KdhcRtjV7soMx5kZJN0pS377p3QUKyATMeUp/Pg8vhByevA/o2lp7SyocXhrXG45on6/twUYYAICAhCVP1trzG3rMGLPLGNPTWrvDGNNT0u4IT9sqqU+t+70lbY8hjmckPSNJI0eOTMffb0BGIXlKf16uPGWFZ09p/HX8+Nfn8P8NAMK4NWzvHUnfDd7+rqS3IzxnvqTBxpj+xpg8SVcFXwcgg+XluPVjK7OcdGTEJqhJ4ZW25NFIpVibKz83W61bsKIJANTm1lnIREkXGGPWKdBNb6IkGWOOMMZMkSRrbbWkmyV9IGm1pDettSuDz7vUGLNV0qmSJhtjPnDhPQBIorzsLD3yzeM1IoZW0H+6YriuO+XIBESVvqyLScHFw3u6duxYufl5AQCSx5VLStbafZLOi7B9u6Txte5PkTQlwvP+K+m/iYwRgLe0bpGtK0/u0/QTIzhjcGDdmpfnbHIypLR2xcjYPmsnZGd5t7pYf5FckiYAyCTU4wGkBE5Rk6dg4gRXj59KCUnqRAoAcIJ3L+8BQC3N6VDevmWuhtca3pdC5+JRu+6UI3XZib1UMHGC7r/kOLfDcVQqDoFLvYgBALGg8gQg7Sy950IVlVVp+L0fuh1KwtROmNJk6asaXm7wFr44ewrmeQCAOFB5+v/t3XusZVd9H/Dvb+68PeOxjWdsz2AbP8bAGD8AY+PE2FBw8INiHkFgp8bCNCZNyYNWClAa0pYSOUJRUAQpchGKW1EoatJCiltiqFqQCAJaHPMK2CIOuLZ4NtBAVdd49Y85Y98Zn5nZc+ecs/e55/ORrLn77HXO/d3rpXv296y11wLmwoEXrTxmtf1qHhlyejrA/FQKwCQIT8BCWG0BY7laZWNPPx3wcM7f/N+H939gwLUCMHmm7QEL4WiucV93xZn5mbNOnFwxE7ZmdWWnucoj7XFfALCaCU8Ah/Hmq5/adwmHtNpG1X46gGl7S2uqUx3zFPQAOHqm7QHMudU2ba+PpcpfdP7+G/N+8Z/8XD77jx63HeGjtmzY+9ljM+QEsFCEJ2AhrLbRmeVW28/Wx2jOu254xn77W21evzY7jt34uHbrl/a+be77ne+rVYgCWAzCE8Ccm8eVCH/7peflZc/YNfbcEKbtHWjXcZv2O14z+p2btgewWIQnYC4cTTzYtH4pJ48ZRVgt5nHBiBsuOS03Pvv0sefWrx3eW9OHX/+z+aO/9zOPHj868tRTPQD0w4IRwKq3bdO67Nl5bN9lTM0cDjwlGT9i9tYX7clzdg9vZcMTt2zIiVs2PHr82MhTG/3bS1kAzNjwPt4D5ta1551y+EZM3Jo5TU/jqr75sjN6nYa4feuGwzfKfI72AXD0jDwBE/P71z89P/jxQ/mzb3y/71KYA0PMfHe+4fL88P/8v4Oef2xhCPc8ASwi4QmYmKU1lZ889PBUXvtIL7SHeGE+LfO4YETy+CXWf+GS03qq5DHHbV6f4zavP2y7x+55kp4AFolpe8BELU1pPtM1RzklcLXthbTcJH+yrtPWJuHAzLduafhvSfv60b7SH12qXIYCWAhGnoCJmkZ4+sJvXpljN62b+OuuFs960gkTe63rn3XqxF5rNfjor16WL3zzrx/3+L7gd/K2jbnnO3+TrRu9nQIsAn/tgYmaxuIFxx9z+GlUi+zkbRtz363X5lc+8IX8yZ8/sOLXueftV2ftDFdCWN5VdmzdkBsvHb90eZ/O3bkt5+7c9ujxJWeekE/d872sXbN3lOwfX7snX//2/84lZz6hrxIBmKHhz5EA5sq0pu1xeO985YX5yj974Yqfv25pzUzvn1o+lfKzb3lBztq+ZWbfe6Xe83eemY/9+uVZt7S39vVr1+RvX7Cz56oAmBUjT8BETTI8vfiCnXnj1U+ZzIstQKZbWlPZvH5+/qzvy2lnnnhMv4UcgWM2rM2TT976aMh8xM1OAAvFyBMwUZMMT5edfWJ2HbdpYq/HMM3DQhEHOnDBCAAWw/y9YwGDtjTBaV8/dWW6qs3zct+PdfP5qx2AlROegIma5D0zpkStbjXHG83u6+fzWDsAKyc8ARM1ydXaLt+9fWKvNaf7yK5qj408zZ93vvLCvOCpJ+WMObpfC4CjNz93FgNzYVL3PN1367VH9XxZafgeu29o/uLT03Zty3tvuqjvMgCYMSNPwEStGehS5bPcv4hujAYCMG+EJ2CihppRNq9fm3/92otdsA/K6L6hnqsAgK6EJ2CihrxJ7nN2b8/xm9f3XQYjjwZZ6QmAOeGeJ2CinvSEYd9A33e0u+3GZ2bjuqWeqxgW2QmAeSE8ARN17EZ/Vg7lzO3H5OwdW/suYxDmecEIABaTaXvARA11wYjh8PvZ59G9knquAwC6Ep6AiZrkJrnT0Hd5fX//IXls5KnXMgCgM+EJmKihDzy5UB8OQRKAeSM8ARO1ZiBXxEMfAeMxzcQ9AOaE8ARM1NBHnmSq4di8fu/iIudYQAOAOWFZLGCihjLydHBDr29xbN+6IR/4xWfnvCdu67sUAOhEeAImavjhqbsP3vLsPPTwI32XsapdetYT+i4BADoTnoCJWjPwycBHku0uOv34rF0a+A80Ae/4+fNz4pYNfZcBAIMnPAETtZpGnhbFKy46te8SAGAurP6PVIGZWk3hyYp9AMBywhMwUasqPPVdAAAwKMITMFFDX6r8SKyiHAgATIDwBEzUUALHpnVLfZfQm5c+fVeu3HNS32UAwKojPAETNZRpe0sHGQI7kurm9Z6n33vlhXn7S5+232O/8/Lz8qV/+sKeKgKA1UF4AiZqKOGJ/W1Yu5QtG/ZfYPWXn3tW7rv12p4qAoD5IzwBEzX0fZ4W1bhMK+cCwJFxmQNM1LxOdVvtWuu7AgCYf8ITMFFP27mt7xIGTbQEgPklPAETtX3rhrm/j+amS0/Pu294Rt9lHB0jTQAwccITMBWnnrCp7xLGuuXyMw/b5pTjNuXa80+ZQTWz06QpADhqwhOwULZtWtd3CQDAnBKeABZUuQMLAI6I8ARMhQtzAGC1EZ6AhdLlzh/LegMA4whPwFTM83ZPFlcAAMYRngAWwLjRtHkOuADQB+EJmIotG9b2XcJYO7Zu6LuEmTB2BgCTJzwBU/EvX31RrrtwZ99lZPeOLfsdP/fJO3L7zRf3VM1wXHzGCbnx0tP7LgMA5sowPxoG5t7O4zbldZeflQ/f9UBvNXzqN56X4zY/fl+nK87ZfsjnrcYFI55+2vH7HX/odZf2VAkAzC8jT8CqdeoJm7N14/hNca8975QZV9OP7Vs35L5br80ZJx7TdykAMPeEJ2Bqhrwgwe+98sL8j9+8su8ypm7A/wsAYO6YtgdMzZCnv61fuyYnrF3fdxlTM+TfPQDMKyNPADPwsqfvSpJs2egzKwCYV8ITMDVDnrZ3oP/yD6/I373sjCRJm8KwzW+/7Lx89Fcvy46tGyf+2uMc6nc/1GXkAWDovIMCJDlz+5ZsXr+UJKkppL6N65Zy7s5tE3/dgzlY/rv95otz9gHLtwMA3QhPwNQcu2n8SndDdcsVZ+UHP3kor/nZJ/VdysQcmAMPt0w7AHBwwhMwNdu3bFjR887bNbsRmuW2bFibf/6S83r53gDA8PVyz1NVnVBVd1bVPaN/jz9Iu6uq6mtVdW9VvWnZ4++oqr+oqrur6t9X1XGzqx6Ypo/9+uV5/y9e0ncZc2/TaAripWc+oedKAGD16GvBiDcl+URrbXeST4yO91NVS0neneTqJHuSXF9Ve0an70zytNba+Um+nuTNM6kamLonn7w1xx5kY1u627ZpXT7+D67IrS8/v+9SAGDV6Cs8XZfk9tHXtyd5yZg2Fye5t7X2jdbaQ0k+OHpeWmt/2lp7eNTuM0meOOV6AebO2Tu2ZOO6pb7LAIBVo697nk5qrT2YJK21B6tqx5g2u5J8a9nx/UnGzeW5Ocm/nXyJwCL41G88z4ayAEAnUwtPVfXxJCePOfWWri8x5rH9LnGq6i1JHk7y/kPUcUuSW5LktNNO6/itgUVx6gmb+y4BAJgTUwtPrbUXHOxcVX27qk4ZjTqdkuQ7Y5rdn+TUZcdPTPLAste4KcmLkjy/HWJHy9babUluS5KLLrrI58sAAMCK9HXP00eS3DT6+qYkHx7T5nNJdlfVGVW1PsmrRs9LVV2V5I1JXtxa+8kM6gUAABZcX+Hp1iRXVtU9Sa4cHaeqdlbVHUkyWhDi9Uk+luSrST7UWvvy6PnvSrI1yZ1VdVdVvWfWPwAAALBYelkworX2/STPH/P4A0muWXZ8R5I7xrQ7e6oFAhNR4+5cBACYU32NPAEAAMwV4QkAAKAD4QkAAKAD4QkAAKAD4QkAAKAD4QkAAKAD4QkAAKAD4QmYGts8AQCrifAEAADQgfAEAADQgfAEAADQgfAEAADQgfAEAADQgfAEAADQgfAEAADQgfAEAADQgfAETE2VbXIBgNVDeAIAAOhAeAIG47Ybn9l3CQAAByU8AYPxc+ee3HcJAAAHJTwBAAB0IDwBAAB0IDwBg/CUk7f2XQIAwCEJT8BM/O4rLjjk+U3rl2ZUCQDAyghPwNRVJWduP+aQbVqbUTEAACskPAFTY4tcAGA1EZ4AAAA6WNt3AQBXnXty3nDlOX2XAQBwSMITMDXLb2OqOvgkvvfc+MzpFwMAcJRM2wOmzr1PAMBqIDwBAAB0IDwBM2H0CQCYd8ITAABABxaMAKZmTSU7t23MG648J4dYLwIAYC4IT8DUVFU+/ebnJ0nuvv+ve64GAODomLYH9GrTuqW+SwAA6ER4AmaixiwZcc5JW/LVt13VQzUAAEdOeAIAAOhAeAJmYtyCEeNGowAAhkp4AnrT0vouAQCgM+EJ6M0jshMAMEeEJ6A3jzTpCQCYH8IT0JsbLj6t7xIAADqzSS4wE2fv2JI9pxybrzz4oyTJfbde23NFAABHxsgTMBMb1y3ljl97Tt9lAACsmPAEAADQgfAEAADQgfAEAADQgfAEAADQgfAEAADQgfAEAADQgX2egJm6/eaL88mvf7fvMgAAjpjwBMzUFedszxXnbO+7DACAI2baHgAAQAfCEwAAQAfCEwAAQAfCEwAAQAfCEwAAQAfCEwAAQAfCEwAAQAfCEwAAQAfCEwAAQAfCEwAAQAfCEwAAQAfCEwAAQAfCEwAAQAe9hKeqOqGq7qyqe0b/Hn+QdldV1deq6t6qetOyx99WVXdX1V1V9adVtXN21QMAAIuor5GnNyX5RGttd5JPjI73U1VLSd6d5Ooke5JcX1V7Rqff0Vo7v7V2YZL/mOStsykbAABYVH2Fp+uS3D76+vYkLxnT5uIk97bWvtFaeyjJB0fPS2vtR8vaHZOkTbFWAACArO3p+57UWnswSVprD1bVjjFtdiX51rLj+5Ncsu+gqt6e5NVJfpjkeVOsFQAAYHojT1X18ar60pj/ruv6EmMee3SEqbX2ltbaqUnen+T1h6jjlqr6fFV9/rvf/e6R/RAAAAAjUxt5aq294GDnqurbVXXKaNTplCTfGdPs/iSnLjt+YpIHxrT7N0k+muS3DlLHbUluG33f71bVX3X8EabtxCTf67sI5o5+w0rpO6yEfsNK6DesxJD6zekHO9HXtL2PJLkpya2jfz88ps3nkuyuqjOS/M8kr0pyQ5JU1e7W2j2jdi9O8hddvmlrbftR1j0xVfX51tpFfdfBfNFvWCl9h5XQb1gJ/YaVmJd+01d4ujXJh6rqtUm+meQVSTJacvy9rbVrWmsPV9Xrk3wsyVKS97XWvrzv+VX15CSPJPmrJL80858AAABYKL2Ep9ba95M8f8zjDyS5ZtnxHUnuGNPu5VMtEAAA4AB9LVXO6D4sOEL6DSul77AS+g0rod+wEnPRb6o1WyQBAAAcjpEnAACADoSnKauqq6rqa1V1b1W9acz5qqrfH52/u6qe0UedDEuHfvMLo/5yd1V9uqou6KNOhuVw/WZZu2dV1U+r6udnWR/D1KXfVNVzq+quqvpyVf23WdfI8HR4n9pWVX9SVX8+6jev6aNOhqWq3ldV36mqLx3k/OCvi4WnKaqqpSTvTnJ1kj1Jrq+qPQc0uzrJ7tF/tyT5FzMtksHp2G/+MskVrbXzk7wtczJPmOnp2G/2tfud7F3JlAXXpd9U1XFJ/iDJi1tr52a0Qi6Lq+Pfm7+f5CuttQuSPDfJ71bV+pkWyhD9YZKrDnF+8NfFwtN0XZzk3tbaN1prDyX5YJLrDmhzXZJ/1fb6TJLjRhsHs7gO229aa59urf2v0eFnsncTaRZbl783SfIrSf4o4zcnZ/F06Tc3JPnj1to3k6S1pu/Qpd+0JFurqpJsSfKDJA/PtkyGprX2yeztCwcz+Oti4Wm6diX51rLj+0ePHWkbFsuR9onXJvlPU62IeXDYflNVu5K8NMl7ZlgXw9bl7805SY6vqv9aVf+9ql49s+oYqi795l1JnprkgSRfTPJrrbVHZlMec2zw18V9bZK7KGrMYwcub9ilDYulc5+oqudlb3i6bKoVMQ+69Jt3Jnlja+2nez8Mhk79Zm2SZ2bv/oybkvxZVX2mtfb1aRfHYHXpNy9McleSv5XkrCR3VtWnWms/mnZxzLXBXxcLT9N1f5JTlx0/MXs/gTnSNiyWTn2iqs5P8t4kV482nmaxdek3FyX54Cg4nZjkmqp6uLX2H2ZTIgPU9X3qe621Hyf5cVV9MskFSYSnxdWl37wmya1t754491bVXyZ5SpLPzqZE5tTgr4tN25uuzyXZXVVnjG6SfFWSjxzQ5iNJXj1aXeTZSX7YWntw1oUyKIftN1V1WpI/TnKjT38ZOWy/aa2d0Vp7UmvtSUn+XZJfFpwWXpf3qQ8neU5Vra2qzUkuSfLVGdfJsHTpN9/M3tHKVNVJSZ6c5BszrZJ5NPjrYiNPU9Rae7iqXp+9q1otJXlfa+3LVfVLo/PvSXJHkmuS3JvkJ9n7SQ0LrGO/eWuSJyT5g9EowsOttYv6qpn+dew3sJ8u/aa19tWq+s9J7k7ySJL3ttbGLjPMYuj49+ZtSf6wqr6YvVOx3tha+15vRTMIVfWB7F198cSquj/JbyVZl8zPdXHtHU0FAADgUEzbAwAA6EB4AgAA6EB4AgAA6EB4AgAA6EB4AgAA6EB4AgAA6EB4AgAA6EB4AgAA6OD/A/8gjoyK5erQAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1008x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "                <audio  controls=\"controls\" >\n",
+       "                    <source 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type=\"audio/wav\" />\n",
+       "                    Your browser does not support the audio element.\n",
+       "                </audio>\n",
+       "              "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.Audio object>"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X, sample_rate = librosa.load(data2_df.path[216], res_type='kaiser_fast',duration=4,sr=22050*2,offset=0.3)\n",
+    "plot_time_series(X)\n",
+    "ipd.Audio(X, rate=sample_rate)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1008x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "                <audio  controls=\"controls\" >\n",
+       "                    <source 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APj/0f/l/+3/8//6/+z/9P/9/wAACwAGAPj/8//o//b/BgAJAAIA4f/l//j/9f8CAAMA+f8MAAAA7P8JAO7/3P8EAAIA/P8AAP7/FgAQAPP/8v/q//P/+v/y/+z/2//z/wEA+f///+3/7//v//j/AADz/wAA8f/z//v/+v8IAPv/BgD9//T/BQDs//X/+//d//z/BgD+/wMA7//m//r/DgAAAP3/6//U//v/FAD7//T/AAD9//7/AAAAAP3/9f/1/xIABADw//r/8f8AAP3/9P8KAAYAAAAAAAAABQABABIADQABAAAA6//r//f/FQATAPv//f/6//v//P8IAAQA+P/9/wUACgAMAAIAAAAGAPv/AgD+/+z/6//3//b//P8KAAYACAD4//v/CgAAAP3/9//0/wcABAAAAAQABgABAPX/CgAWAP3/9P8CAPv/9//1//L/9f/u//7/DAAOAAcA/f/z//f//P/6//T/7f8FAAAA+/8EABMACADr//7/AwAPAPr/+P8MAPf////y//3/EwAAAAcA///5/woA///7//3//v/9/wEAAAD2/wEA+//z//H//P8JAPn/+P/u/+///P/y/+//+v8HAAQACwACAPX//v/7//7/6f/t//v/6P8JABcA///x/+//+P/8/wkADQD2//3/BQDy/+7/7f/t//j/+P/z//b/BgAFAPn////7//r/+P8EAAIA5P/x//r/9//+//v/+//v//r/CADw//7/+f/u/wkA7v/l//L/7P8GAO7/3f/9//n/BAD+//D/+v/t/9///f/5/+//AwDz/w0AEQDz/wAA9f/v////9P/v//L/7v8FAP3/8P/6/+f/8v/3/97/6f/y/+b/8P/5//b/8P/y//v//P/v//b/AADu//b/8//r//z/7P/k//X/7f/y/wAA8f/s//r/BwD3/9//8P/t/+T/9v/y//z//f/k/+n/7P/l//f/7P/j//z/9f/6//L/4v/3//r/+f/3/+v/6f/4/wEA7v/2/+3/4v/4/+b/4f/2//n/7P/6/wUA3f/X//r/8//i/+r/8f8AAAkAAAD4/+T/3P/v////9P/n/+b/7P/k/+X/9f/7//r/6//m//H/AgD3//j/BADx//P/4P/v/w0A8P/j/+v/7v/v/wAA8f/t//r/7f/3/+X/4v/0//H/7v/j//P/9v/y/+3/6//y/+T/8//8//j/8v/z/+z/3P/2/wEA7f/j/+////8BAOz/8P/6//v/AAD2//P/7//1//b/9P/9//L/9v/r/+z/AQD0/wgA9v/e//H/7f8AAAAA9//4//P/9f/w/wEACAD2//X/9P/z/+3/8f/v/+f/8P/1/wgA/P/v/wAA8//3/wkA8//q/wAACgD4//T/CAD2/+z/8//+//r/9/8MAPr/AAD9//v/EAD3/+r//f8FAO//6v/2//3/CgD8/+f/5//8/w4A8//i//L/7P/5/wAAAAAPAP7/+v8IAAoA/v8AAAAA8/8CAAUA9f/3/wAADgAEAPv//P/2//z/AAD+//f/7P/r/wAAAAD9//z/+P/8//3/AAAEAP7//f8UAAoA9//v/+X/CAALAOn/9v/0//b/CQACAAQABgAAAPX/AAD9/+b///8AAAQA+v/q/wIA/v8RAP7/7f8CAOz/8v8MAAgA/P/4//r/CQANAOr/3/8NAPn/9P8SAAEABQAEAAQAAwABAP7/CwAFAO//DgASAPv/8//9/wAA8//1/+7/8//6//3/AAACAAYA8P/1//3/7v/+/wEABQAHAPT/BgASAPj/8v8AAPb/7v/+/wQA+//6/wIADwAUAPz//v8DAOf//P8EAPv/EQAMABAABwD+/xIAEQD7/wIADQD0//v/DAAEAP//AAAFAPX/8f8MAA4ADAAKAPz/CAAEAAUAHgALAPz/AAAAAAwAAAAHABUABQAFAPr/CwAPAPv/EQAJAAgAEgAFAA0AEgAVACEAFgACAAUABwAMAAwA/v8QABYADAAOAAgAIQAJAAEAIgACABEAHwASABUAAwALAC0AHAATABMABwAYAA0AHQASAAIABgAKACAAGQAYABIAJwAqAB4AHAATACAAIgAXAB8AKwAYABgAGgAVACsAOQAaABEAKQAfAB0AIAAkADYALQAxADMAHQAvACYAJwA1ABgAJQAlABEAMgAnABsAOQA7ADUALwAjABsALQAdAB4AOAAoACMAMQA2ACsAOwAzADMAIwAsAFMAJwA3AEUAKQA+ACsAMQBYACgAHAA+ADgAMgA6AE0AOQAxAC4ANwBAACwAMwAmADIAUABLAEwAOAAvAEUAQAA2ADAASABQACoAGwA7AFsAPAA1AEoAQwBNAD8AGgAjADoARgBJADsAMwAwADUAQQA4ADgARwBEADwAMAA8ADoAKABCAC4AGgAvADgARgA9ACwAOgA+ADsANQArAEcAQgA/AEAAJgA6ADcAMQA8ACMARAByAE8APQBKAFIATQBPAEMAQABAACoARwBIAEoAUgBCAEYAQABNAEwAPwBDAFEALQAnAEIAOgBDADQAQwBKADsAUAA/AEQAWABAAEMATQA5AEIASQA8AFMATAA2AC4AKQA/AEgAKQA1AEgARgBWADcARwBVAE8ASAAvACgANQBeAEAASwBSAD4AXwBQADEAKABOAEoARgBoAFgAOgA7AEQAPQAxADAAVwBrAEsARgBcAEoAYQBrAEoATwBWAFIAVgBmAF0AXwBNAEwAVwA3AD8ARwBVAHMAWwBCAFQAVwBRAEgAUgBRAEgAYABLAEoAZABjAEMARgBXAEcAYQBQAFoAcQBMAGwAbQA6AFUAcwBAAEkAeABVAGIAXABBAE0ATQBPAE4AcwBnAFIAdgBxAEQAWABeAFcAfwBNAFwAdgBJAGgAbgBdAFIAUgBfAGcAZwBaAF0AcQCIAHQAVABdAFQAVwB3AEUATQBvAFQAfwB6AF8AXgBdAGgAXwBQAGIAZABRAF4ARABCAGsAYwBoAG4AUgBqAF8AOQBiAG0AVwBaAGYAaQBVAFwAjwBrAE8AbQBcAHEAWQBnAHoAUwBuAGYATQBDAFYAeQB2AFYARwBkAHAAVQBTAGAAawCGAGkAVABeAGMAegBWAE4AbwBZAGYAiQB+AF8AbABqAFYAXABbAGkAcwBsAFYAQgBTAG4AYgBVAE4AdAB6AFMAbQCBAIQAfAB8AHoAZwBjAG8AYwBgAHQAXgBWAG4AYQBHAF0AcABjAGQAYABmAHYAWgBtAHYANABeAIgAaABsAFwAcQB4AFEAXgBbAFEASABRAHYAYQBdAHwAWQBKAGQAYgB/AHEATABjAF4AXgBvAGAAbQB8AGsAhAByAGIAjAB5AGAAeQCMAGAATABjAGUAVwBJAFoAfQCKAHEAbAB1AHsAcQBwAI8AiABhAGEAZQBpAHIASQBMAE4AUQB+AG4AaACKAIoAfwCNAHIAawBvAFQAbwBfAFEAZgBaAEcAYgCUAGcAXgB0AG4AigCHAHMAYABbAGsAYwBnAHQAWQB5AHQATABqAGkAXABbAGkAeABbAE8AgwBxAGkAhwBdAGMAYwBaAG0ANgA/AIcAcgBRAFIAYgBeAE0AVQBsAFwAbwCFAF0AewBpAFEAaABRAD8AOwA/AHIAdQBBAFQASwBNAIoAYgA5AGIAUwBYAGkAYQBgADAASABzAGIAZABTAEkAZABpAFUAcwCAAGoATwA7AFsAWwBbAEwANAA/ADQALwA9AGMAdwBZADkAYgB7AFwATQBAAD4APQA4ADoANAA8AEgALwBAAFMAQAA4AC0AUQBjADcAQgBgAEYASABLACAAOABUADEANgBAAC4AMQBLAE8ARgA7AC0AQQBCACQAOABEADMAIwAZAD0ANQARACwASwBKAFMANwAkADYAKABLACUAAAA7ADgAZwBMABUAMQA0ADgAIgAdACgAIwAfADsAQwAiADAAUgA8ABYAKABMAFcAXQA4ACMAIQAsAFsAUgBvAGMAMwBPAE0ARABLADIAEwAfAEMANQAhAEEASAArABwAOgA7AC4AOQAYABkAVQBFADsANgBBAFMADgAvAE8ASAA9ACAAOABJADgAFAASACwAOAAwAB4ADwA0ACQADgAsABMAKAA5ACcALgA8AEgARAA7AEEARgAiACMAQgA8AEYASQAwAEUASAAdACkAQgBXAFwAOwA1ACoAFwA2ACQAJABIADoAIwAoAF4AVQAyABYAOwBnACsAKwBPADkAFQAHAA0ASABNACUAQABWADwAKgA9ADkAMgA+AE4ARwAvAD4AUgBBADYASQBKADwASwBQAEIAHAAKACYAPQBCAEMAVQA0ACYAMgA9AEcAQABeAEcAGAAiAEAAOAAqADQALgA2ADEASQBtADUALQAcACAAQwASAEAAXwAyACQAJwBQAF0AOAAtAEAAPQA9AFcAMgBNAGkAJgAqACgAMQBLADQAMABBAEIATwBVAE4ARAAtADEATABEADIAOAAqAEMAKQAkAFIANABWAFAAIgAnACgATwBaADwAPQA3ADMAQgBRADgAOAB5AFkALAA7ACIANgBdAE8ARAA0AEYAVABIADoAKQA4ADcANAA+AFwATQAUACoAQgBBACkANgBVAEYAWABWAEwAQAA9AEwASQBJAGIAcwAsACkAWwA+AFgAVgA4AGEAUQBNAGEAUwBKADoAMwBGAEcAKgBKAEYAIgBvAFMALABeAE4AXAA6AEEAagBQAEwAWwBSADIAWABwAFUAVQBrAFEAZABjADcAVABWAEEAPwBUADwAKwA+AE8AaABUAFsAbQBQAE4AVQBdAGAARABYAFoAQwBEAFoAawBtAGEANwBVAGUAWgBuAEEATgBnAFUAZgA/ADAAVwBhAF8AhgB3AD4ARgBEAF4AbABGAEsAWwBUAFwATgBOAGUAXwBiAGwAfgBpAF4AdAB+AHMAbgBpAD0AZgCFAFsAfwB3AE8AbwBxAGoAaABlAGQAZABbAE0AZwBdAGoAggBJAF0AdwBuAHsAXwBkAHAAcgB7AGkAgAB+AGQAeQBgAHAAdABKAHMAgQBtAE8AUQBwAHAAegB8AIUAkABzAF8AYQBdAGYAbACAAI0AawCBAJEAdgCOAHwAVABpAIMAmwCQAG8AegCQAIEAYQCCAJcAggCUAJAAhQB4AIUAkQByAHcAfwCLAJcAdwBwAHwAXgB/AJYAggCSAG0AeACZAHkAdwCXAJoAjACVAH8AagCAAJgAkQB7AIMAjwCEAIIAggBoAHYAhAB6AIQAdgB6AHEAYgCNAIYAegCfAI4AjQCCAJEAsQCGAHkAhACdAHkAYgBjAF0AhQCDAIEAcgBkAIUAjABzAH4AiwCMAHMAXwB1AIAAdgCEAIUAdgCKAIcAjACHAIMAiACIAIAAewCHAHUAigB9AI4ApAByAIoAlQBsAGEAegB+AIwAeABzAKAAgQB1AHYAdQCZAH8AbAB1AHEAiAB3AHkAeQB5AJcAhAB7AIAAlwCHAFcAdwCHAHcAgABtAIcAjgB+AJIAbABoAEwATQCjAIYAVwBuAI8AnQCQAIwAmgBxAGAAcABdAH8AdAB1AJUAYwBuAHwAdQCKAHUAcgCIAHsAbwCKAHcAYAB+AHwAXwBTAGAAeQB7AHIAigCIAGoAfQCdAJwAkQCUAIkAfQB3AHgAewBaAFYAgwCRAHQAdwCLAIYAbABxAJIAnACbAIIAggBwAGwAjACBAJoAmQBRAFcAcgB2AIUAcAB9AJAAgQB+AHgAjQCMAGEAXQB6AJgAggByAJkAmACFAIUAaAB7AI0AcwCFAJEAnQCjAH4AfwCUAHsAcwCSAKIAkQCaAHQAZACbAIoAiQCVAJsAoACJAIMAhwCMAIUAmQCgAIgAmQCVAG8AkACvAJoArAB2AIUArQBzAIEAewB+AJAAiQB1AGgAeACYAJgAlwCrAH0AgwB/AGYAigCGAJIAqACMAF8AeQCeAHUAfwCGAHwAkQCCAJcAiAB8AKwAmACNAKUAmQCQAJ0ApgCWAHMAjACtAK8AgwB1AJ4AegCVAKYAmQCiAJsAjABpAJoAowCFAKUAjgBwAJMAkgBzAJEAhwCAAIoAewCiAKIAiACKAGQAfwC7AIwAmQCbAIgAmACBAIsAkgCXAIMAkgCdAJcAwwCvAJoAlgCGAJEAmwC0ALoAmAB1AJEAtQCeAJ4AiACQAKEAiQCJAHwAigCoAJUAfQCBAKUAvgCdAIUAggCOAJcAoAChAJQArwCWAHoArwCyAJoAlwCgALkAoQCTAJEAhwChAK0AoQCdALoAqgB5AH8AdgCLAJ0AjQCUAIAAfwCDALEAtACMAK8AqQCfALMApACiAKMAlgC3AK8AkgCLAJEAsgCgAJsAnwCTAJ4AjwCsALIAjQCuAK0AqACzAJ0AtQDJAKUAoACyALEAuQCqAK8ArAB5AJQAmgCcAMkAtAC4AL8AvQDFAKUArACkAJoApwCbAK8AmQCsAKoAmwDBAKUApACpALEApQCaAKEAnQCkALAAsQCyAL0AsgDMAOAAmwCCALoAsgCzAJsAoQCwAIUAtwCqAKYAvQCUAKkAxwDCALwA0wDKAKwAwQDfAMgApQCyALUAuADNALkAoACuALYAqQCIALgAzwC2AMcAtADCAMEAsQCzAL0AvgDHAMEAsQDOAMYAuwCnAMUAxQCdALwApgDFAMUAlwC5AKQAmACVAJoAswCUAKoAyACmALAAyQDFAJcAqwDeAKgAtQDAAK0ArwCWALEAyQDVANAAuQC8AMIAtQCaAK4AxwCmAIUAmgCwAKMAnwC7ALMAkQC3AMIAvQDOALAApwCoALkA1AC0AK4AvwCgALAArwDJAOgAlQCOALYAuwC+ALIAqACvAKkAxgDNAJ4ArQDEAMIArgCrAL8A0wCpAIwArgC5AL0A3QDMAKgAwwCpALQAwwCyALEAmACcAJ0AlQC0AKMAkQC0AKMAwADKAKkAtAC9ALsAqgC8AKYAmwDNAKkAjQDFANsAzQCuAIoAuwC+AJkAtgCnAK0AxQDGAMoAugCXALIAwwC3AMMAtADHAL8AvwC0AJ4AzwC5AKIAtAC5AMYAwwDBALUAowCYALIAvwCkAKgAuwCmAL0AxgCeAMEAuwCcALYArACLAKIAnACaALYAuACiAKUAywCTAHoAlACjALIAmwCQALUAqwB9AK0ArwCIAJcAngCvAKgAiACPAKUApwCfAJgAfQCKAKgAmgCRAIoAlgClAIwAgwCtAIkAmAC+AIAAtACzAHcAkgCEAK4ArwCCALAAlQB/AJcAlwCrAK0AhgCPAKcAtgDRAKIAkgCcAKQAogCEAIsAiACiAJoAjQCcAIQAqQCmAH8AkACNAKAAmgB2AJMAgACJALoAjACOAKAAfACAAI8AnACeAJIAjgCJAIcAjwCSAIAAeQCYAIoAggCYAJMAqACaAIsAhABqAHYAkACJAGUAdgCJAH8AlwCJAGMAewCQAJAAhACEAIQAiwCdAHkAZwCLAIwAiwCYAIYAjgBvAHIAkwByAIAAggBqAHsAhwCgALoAjwCBAJQAhgCAAIcAlACZAIIAmwChAHQAgACaAJ0AegB5AIoAmACTAJAAoABuAIAAngB1AIcAqQB/AGgAfAB0AHwAkgB5AGoAfACJAJ0AkwCPAHIAYQB7AHcAjwCiAI0AdwCEAIMAkwCKAFsAggCaAHsAgACWAIQAgACFAIYAkQCZAIMAbwCWAIEAhgCQAH0AhwB0AJsAhgB/AJEAfQCJAHUAgwCMAI4AeABpAIAAhABzAF0AYABnAIMAaABdAHIAcACFAH4AdwB5AH8AkAB+AFQAewCRAIwAnQB8AHEAiQCUAJcAkQBmAHwAfwCFAK8AfwB+AJgAfwB+AJkAgQCHAIsAdQCiAJ8AngDGAJ8AkACZAH8AiACFAH8AfgB/AH8AdAB9AIoAeQCCAIYAcgCgALAAngCIAHAAewCaAKEAmACRAI8AogCAAG8AigB/AH4AfgB0AH0AiQCDAIIAhwCUAK8AkQB8AKAApACgAIcAgQCXAIkAeAB5AKEAmgB+AJIApAB8AHsAlACGALMAwQC2AJcAhAC2ALIAjgCQAJUAkgCVAJYAlAChAJoAmgCpAKMAnQCfAKQAhwCPAJYAhACmAJMAtwDTAJgAsQC1AKIAqQCfAJ8AogCfAJ4ArwDEALcApgCyAJAApADZAK0AiwCUAK8AuwCtALQAsQCbAK4AvQDCAMQAswCbAK8AzACgAKgAqwCqAMoAyACZAKUAyQCmAMkAzQCfAJ8AsQC4AKAApACuAJUAlQCZAKkAuwC1AKsAsACoAIUAtgDVAK8ArQCzAK4AoQC5AOAAwQC8ANoA0QC1AJ4AzQDcAKUAswC4AKEAugC9AMYA2gDJAMkAxgDNAKwAmgDNAL8AwwDPALgAtwC4AMkAvwCyAMIAwwDIALUAtgDXAL8ArwCwALkAzgC8AKsAwgDJAMAA1ADpANEAzgDoAL0ArwDFAM8AvACpALAAvgDcALQAqgDHALsAywDyANIAsQC9AMsAvACuANQAoACpANEAvgDXANYA2gDKALkApwCqANYA1wDZAMYAsQDYAN0A0ADFAM4A1wC+ANUAzAC+ANUAxQC9AMcA1QDiANoA0QDGAMIA3ADTALkAzgDMALoAwQDVANYA3QDAAKYA3ADDANEA2wC1AOEA2wC7AK4AyQDcAMQAywC3AMAA4wDZAMEAtQDVAOQA8gDlAMQA5ADZALgA5gDVALYA2gDcAOoAzQDOANcAwADfANYA5gDoAMQAwQDXAOoA3QDqAN4AyQDdAMoAuADYANgA3wDnAPEA6ADgAOgA3gD2ANsAvwDTAOUA3ADhAOQA1wDqAOcA2ADMALsArADRANgAxADWAOcA5wDPANsA0QDGAMIAtQDlAN4AxgDLANkAxQCzAOMA5wDOAMEA0wC5ALgA5ADHAKMAugCuAKUA1gDQAMAAxADDAK4AqQCoALUA5gDXAMYA5wDYAMAArwCoAN8A5ADCAMkAswC+AOcA4QDCALMA0wDJALcAzwDXAMwAxADbAMcArwC1ALIAtQC0AL0AuQDTALsAtADbAL4A1QDbALMAuAC9ALwAvQCyAKsApQC9ALQAvQC4AK8AyQDCANQAyAC5ALMAsQCnAJcAlAC5AMAAkgCLAKIAuwCzAK0ArwC/AKcArgClAJcAtQCkALIAqgCvALQAvwCxAJ0AuQC1AKMArADMAJ0AkwC3AJwAqgC+AJ8AkgCxANcAvACRAKQAkQCjAKMAgAC4AJUAjAC3AJwAowChAK0ApwCfAJ4AnACaAIYAnwCbAK4AmwByAJ8AkQCUAKYAfQCWAKEAjgCcAHkAgQCOAJIAnwCPAKMApQCCAIAAkgCjALIAmQCbAKYAjwCWAKIArACrAJ4AlwBvAI0AfgBzAI4AdwCiAIEAfACKAIUAmwCGAHkAlgCKAIEAugB9AGgAeABsAJsAkACUAIwAUQB+AIwAcACDAHoAcgB1AI8AjQBtAHcAdQBbAFsAZAB8AIAAcgBZAFsAegBrAGYAWAB1AIAAewCEAHUAgAB3AHoAfwCWAIsAYgCCAJIAagBdAGwAawB3AG4AWABoAG8AXgBtAGsAWgBaAFIAYABaAGcAagBrAHwAZgB4AG8AXABQAEwAcwBvAHwAdwBRAFcAZQBuAGoAaABcAE4AQgBbAGkASQA1AC0ARwBfAFkAWwBVAFEAZQBcAGwATABAAHEAQwA+AIAAdQBFAFsAawBpAGkAbgBmAF0AWAAvAEgAYgA6AEQAbgBPAC0ASQBQADUAWQBoADAAMwA6AFAAYQBSAFAASgBQAEYASwBRAFUAYwBkAFAAOQAyADwARAA9AEQARwBZAFsARABKAEoASwBAADMANwBXAGoANgA9AE0ATgBWAD0ANwBPAF4AVgBfAEoARABHADkAQwBOAE4AQQBDADkAQABWAFoAQQAqAEAARABeAFsARQBVADMAOgBlAFgAOQBIADgAHwBPAFYAOwA5AEcAQgAyADIATQBPACAAJgA1ACwASwBhADwAKAAxAEIANwAnAEcATABFAD8ANQA6ADkAKgAxAC4AJAA/ADcAIwArADUAIQAdAEoALwAuAEsAJAAtACcAEgAlAD4ANwAhACcAHAAoAEcAGwAIAD8ARQArACgAMgA2ADcAOgAhABsAHwAmADMAHQAcACkAIAALACoAQAAfADIAPAApAC0AMgA0ACgAFgAlAC8AJQA1AC4AIgAqABoAKAA7AA0ABAAJAAwANAA2AC4AFAAaACUAMAAuAA4AKwAdACcAMwAaAC8ALwAoACUABwAgACUAFgAyAAoAFwA0ABgAIAAbAP3/AgAnAA8ABwA1AB4AGgAzABwAEAAFAAsAFwASACwAJAAYABkAEQAXAAkADgAqACkAJwA1ACAADAAgAC0A9/8AACIAEwAoABwAHAAeABkAMwAZABQAKgAYADAAHwAZACwAFgAqAEEAOAAZACcAPAAtAC8ANwAgABYAKAAuACwAKgAeAB0AHwAeACoAKwAZABgAMwAmABoAGgAgADMAFgAcADEAIwAwABkABwAWACYAMAANABYAHQAYACoAMAAyACEAMwAkAAYAGAAiACQAFQAcADIAGQANADIAJgAzAC8AGQAyABEAHwAqAAwADQAMABgAFwApADkAHAAXADsAPAAbABMAFQASAA8AJgAiACUAFQAaAEMAIgAmADAAIAAQAAwAGAAlACUACQAeACsAIwAxACAAKAAzAAsAEwASAA8AOAAhACUAJgAPACcAKgA2ADcAIQAhADIAFQAHACgAFgARAA4AGAA/ACoABwALABwAJgAUAB0AKQAKABkAIQAqADkAFgAYACMAIwAmAC0AKwAoADMAKAAxAB4AFwAuABQADgAZABUAKgAiACUANAAaABwAJgAcAB4AOQAfAAkAJwAmAD0ANAAfADkAGQApACgAHABAAAsACQAZAAoAFwAdACkAFgASACsALwAbABkAIQAZACUAFwAWACIACQADACAAGAAbACYAHAAvACwAQgAoAAQAKQAgACsAJgAPADsAOQAkACEADQAZABUAKwAyABMAKgAjAAwABwAeAC4AHwBAAEEANgA4ABwAJwAiAAsAIgAsAB8AHgAxADEAHwAtACQAKwA/ACIAIQAqACQANwA3ACAAJwApAA8ADwAqAC4AHgAeADYANAANACkASgAdACsAMwARACIAMgA5ACIAJgApACUAQQAeABcAKwAeAC4AQQAeAA4AIAAnACYAIQAfACoATQA4AB8AMQAhACAAHAAaAEIAJQAAABgALwA7ABwADgAzACcAIgAkAP//FgAgABgAKAAjABsAAQAYADkAKAAlACUAGgAbAC0AJwASAA8AIwAvACsAIgAcACsAJwAbABAAFwAUAAwAFQAgADcAEgAhADEAKgA8ACQAHgAPACkASAAuACIAIgATACUAIAATADMADQAWADcAJQAjABUAEgAZACEANwAaAP//FwAMABMAFAASACIAEgAcABQAAQARABUACgAIACMAHwAYADAADAAKAC0ALwAYAAwADAAYAB8ABwATAAcAHgAgAAUAJgAZAA4AGAAjACEACAAHAAMACQAeABoAGwD9/wgAKAAcABIAFAAYAAUAHgAQAPn/FAAKAAYAJwAcABUAHwAQABQAGAAZABAAEwAMABUAGQAFAAsAAgALAA4AHwAcABcAKAAIAAMABQAFAAwABwAWABgADwAVAP7/AwARABAAIAAGAAsACwDy/wQAGAAlAB4AJwAXABIAGwAAABYA/P/5/xoACAARAAsAFQAVAAcADgD//xQAGAAOAAIAAAAeAAgACgAJAAoADAD1/wkAEQARAP//BAAIAP3/JgAAAO3/BQD7/xcACAD7/xoA9/8BACsACAAOAAYAAAATAO7/CAASAPn/DAABAP7/BAAWACYACgD6/w0AFAAGAA8ACgD2//n/DgAjABMACAAQABUAEAAGABAABgDz/w8AHQAUAAQA9/8FAPT/7f8CABAABwD3/xQACwD+/w8A+f/9/wAAAAASAP////8GAAYABQALABkACQD1//T/AAD5//f/FgAbACAAGAD7//z/+f8LAAsA+/8LAOn/8/8AAPv/FwAAAAYACAAOABMA+v8CAP//DgAIAPL/AAAHAA8A/v8AABMADQAHABkAEgD5/wUABQARAAQABgALAPT/+//8/xIAJwAHAAoAFAD4/wIAAQAIAB8AAQAOAB0A+/8AAP3/BgAlABUABAAQAAsA//8DAAcAJQATAAoAJQAlACcACAD9/w4AFAAMAAYACgAAAAIAFQAJAAAAEQAVACAAFwAWAB4A/f/7/wcAFQAUAAcAHgAWAAcADwATABsAJwAbAA8AGwAVABAAFwAPAAcAJAAfAAYADQAPAA4AEAAfAA0AEAASAAQAFgAOABcA///y/w4AEQAkACgAGwAJABEAFgAHABQAGwALABEAEgAeABMAAgAoABkAGgABAAYAKwAPABgACwAcABYAAQAwAB8AEQAkACEAIAAdACUAIgAWACEAEgASACUAFwASAAAACwAkACEAKQAdABYAEgAKAAcA/v8FABIAEwARAAcACQAOABoAJQANAAwADwAMABMAEQAbAAQACwAQAAwAKAAAAAUALwAgAAkAEAAfAA4ADwAIABYAHQAAABQAGQANAAYAAAAOABEAAwAMABEAAwAGAAAA/v/+/wkAAAD4/wAA+f8ZAAwA9f8GAAQAAQD0//n/CwD7//z/CAD8/wAAAQD7/wYA+//v/wMA/f/+//b/8f/4//b/CgD4//H/BQD1//7/CwAKAAwABAAPAOb/4//3/+v/FQACAPj/9//5/w8ABgAIAAMA9//3/w0ABADy//T/+P/p//v/+P/3/xQA/f////7/AgAMAPf/9P/x/+//AADv/wIAAgDw//7/9f8IABQAGAAHAP3/7v/r/wAA9/8EAAEA9P8JAAMA5P8AAPn/6f/w/+L/7v/1//r/5//x/wAABQD8/93/9//2//j/BAD5//T//v/y/+7/BQDy/97/8//7//7//f/2//z/4//0//D/2v/4/+b/6//z/+f/9//m/+7/+P/g/+3/BwAJAO3/6//w/+j/8//g/9j/8v/w/+n/+v/2//P/7//u/wQA6//f//T/6f/y//T/7P/v/9//3P/g/87/3/8HAOr/6v/8/9D/0P/g/9n/4v/i/+f/5P/s/9r/vf/M/8b/8f/u/+P//P/d/97/xv/E/+f/1v/a/+D/0P/e/9b/z//n/9v/1f/W/+H/4f/R/+n/5//Z/9v/2//h/9X/0P/V/+L/2//L/+X/5f/X/8D/uP/Y/7z/xv/d/8P/vf+//9P/x//b/+z/uP+x/7r/yf/A/73/zf/J/8L/vf/M/8L/wv/D/7r/y/+//7//x//N/83/sP/V/8T/uf/b/7f/yP/J/9L/3//D/7v/xv/U/8H/2P/T/7n/zv/H/7b/x//g/73/vv/R/7b/yf/a/67/pv/Q/9f/zv+u/77/4v/O/73/vf/L/8T/tP/A/7j/qf/B/7j/uf/D/7T/tv/K/9D/rf+9/8L/zf/L/7z/zv/L/8z/zv/S/8r/4v/T/8P/1P/C/9H/0//E/77/yf/H/7z/zf/B/7T/wv/Z/9P/w//D/8T/wv+7/8f/0/+4/7n/5v/k/8f/0//U/9D/6P/M/8f/0f+z/8f/0v/H/9D/wv/J/8X/tP/B/8f/yP+9/8j/zv/B/87/zf+2/8b/x/+7/93/3f/b/9//uf+0/8T/w//S/8P/1P/Q/7P/4f/i/9T/sP+t/8X/w//T/73/uf+6/7v/p/+8/9L/vf/b/8b/wf/X/8n/xP++/6//u/+9/7//1P/F/8v/yf/N/9D/v/+6/7L/zv/w/83/u//Q/7z/yv+5/7z/3/+//9z/z/+o/8z/yv/I/8j/w//S/8X/0v/F/7z/3f/C/8X/1v/M/7X/uP/H/8X/1P/b/+X/5P/V/7H/zP/h/8v/3v/L/8j/3//Z/9z/0f/T/+H/vv++/8j/x//Y/+b/0P/V//n/wf/A/8z/wP/b/8X/2//g/8X/2P/Q/7z/2f/k/+H/3v/G/9b/1v/d/9v/4//0/7X/t//c/9D/2P/o/93/tf/d/+D/qP/g/+L/2P/k/8//3//S/8L/3v/V/83/1//L/73/vf/R/9f/3v/T/+r/4P/U/9v/0//h/8P/1f/g/9n/4P/D/8j/2//J/+r/+f/U/+//7P/C/73/5P/9/9//1v/L/8n/5v/v/9z/w//W/+P/5f/a/8j/4P/s/9b/1//3/9v/2f/p/8T/1f/n/8n/1f/X/9T/4f/O/9n/7//d/9j/3f/m//T/4//q/9j/w//2/+z/2P/8/+n/5v/m/93/5P/P/+L/3f/r//v/2P/Z/9n/4//i/+f/CgDv/+n/+//X/+3//P/g/+v/8v/m/+r/5f/y//v/7f/v/93/5v/g/8z/2v/S//j/9P/R/wUA7//j//b/2f/7/wQA9f/n/+//9//p/+3/3//u/+b/3f/1/+v/9/8FAOf/2//t//f/+f/2/wIA6//s/wYA5P/g/+n/9P8KAOv/4v8AAOj/6/8BAPP/5//r/+j/+v8kAAYA6f/y/+z/4//z////4v/5/wEA+f8ZAPr/6v/q/9z///8NAAAADgAKAO7/6v/u//7////8/wUA9v8LAB8A//8DAAQA6P/u//b/AAD//wIAFQD+////AwD3//j/7/8JAAsA/f8RAAsAAwD5//L/AAD+/wMABQAAAB8AMAAAAOn/BgAOAAQACwAFAPb/EQAXAAcADADy/wUACADg//j/+/8AABQAAgD6//n/5//7/woABQABAO3/9v/7/wIACgD4/+j//P8IAPf//v/4/+j/8P/v/wUABgDj/wcACgD8/w8A+v8DAAEA3v/n/w0AGQAIAAsADAD+/+z/BQAXAPz/+//1/wsABQABABEA9f8AAP7/9/8AABkABgDs/xEACAAGAP//1v/j/wYA/f8BABUAEAAWAPz/6/8AAAwABQDv//j/7f/s/xMA/////wAA8////xEADQAAAAQA+v8EAAUACAALAPn//P8NAP//CQAXAAAA9P/w/wkA/v/8/wsA/v8HAAcAAQAAAP3/AAD4/wIAAQD6////6//y//n//f/9//n/EgAAAAEABAD2/wgA+f8WAAMA6f8UAAkAAgD2/xoACgDb/w8AAQDy//v//f/5//r/EgD6/+L/+P///+n/8//g/9n///8HABYAFAAJAP//4v/w/wIA1//0/xQA9P/3/+3/AAAPAOv/+f8EAO///P/8//X//P/d//L/CADk/+v/1v/x/wIA1f/v//r/4f/T/+r/+P/p//H/9P/s/+T/5v/q/9j/2//6//b/5P/m/+z/5v/l/+b/6f/u/+j/7P/a/+f/AADg/9n/3P/V/9X/3v/n/+X/4f/h//P/5f/m//D/6v/q/+X/4P/R/+//8//k/+7/6P/s/+//+v/1/9z/4P/l/9//5//W/9n/9//9/+H/0v/u/+3/1v/H/+b/5P/O/9b/xv/Q/+L/z//N/9T/3f/x/+P/0//O/+T/9f/U/83/6v/R/8v/1//E/9P/6f/w/9r/0P/Z/9v/2v/b/+r/5P/U/+b/3f/D/8v/0P/F/9D/7f/Z/7v/zP/v/+D/x//Q/9D/2v/m/8f/1P/r/9P/z//c/+f/0f/P/8//3f/i/8n/3/+8/8//3f/R/+7/x//a/8H/s//S/8X/xP/J/93/uv/G/+D/wf/A/8P/xP/E/8f/1f/R/8D/z//P/87/zf/B/8z/1f/M/8f/z//R/9P/wf+9/+H/zf/H/+D/0//E/8f/0f/K/8n/0//Q/8X/0f/S/83/zv/Z/97/v//T/9j/zP/Q/8H/xv+1/7X/w/+8/7r/x//W/83/wf/P/9D/vP/F/8f/xf/U/8f/xP/D/7n/w/+7/8X/yv/F/8v/5f/h/7X/vf/I/8r/yf/J/8T/wP+//7z/wf+9/8//x//B/6v/qv/H/7b/zv/A/7z/2P++/7v/0P+3/6D/x//e/8T/uf/M/7L/uv/X/7v/tf+//8T/wv/C/8L/yv/L/9T/0v+5/9H/xv+//9r/y//K/8T/rf+7/9H/yv/F/8//yv/H/9L/0//T/9v/wv+//8L/zP/u/83/wP/K/8b/xf/M/8T/1//i/77/1f/V/9v/3P/J/+n/0P+0/9j/2v/M/8T/x//e/9T/0P/h/9L/yv/X/9j/1f/c/9b/y//f/7//tf/g/87/w//O/8r/0f/N/8X/yv+//8z/3//P/83/x/+//9b/2P/I/9r/4f/T/97/4P/d/+X/2P/X/9T/zv/m/+P/6P/p/9r/1f/I/9v/6v/a/9r/5P/c/9r/1v/O/8z/1P/U/8z/2v/u/+L/4f/j/8v/yf/D/9T/0P/N/9z/y//R/9D/yv/R/9v/3//m/9f/y//f/9L/0f/U/9b/8//g/8X/yf/b/+3/3f/T//P/+f/i/+//5P/n//f/4v/b/9P/1v/l/9P/xv/V/+L/3f/V/9X/6P/y/9H/zP/R/9X/9P/V/8v/2P/F/9b/3v/m/9b/yP/i/+n/3f/V/+P/5v/f/93/zv/Y/+3/2v/X/+n/3P/U/+X/5P/a/+n/6f/g/+7/3f/X/+v/5//i/8//z//e//T/8v/m/9//2//0/+n/4//i/9T/2//X/9//6//i/9//3v/P/93/5v/R/9v/3//R/9H/2v/l/9T/zf/g/+L/4P/W/9P/7P/q/+z/8P/e/+j/3//c/9v/3f/1/+D/4v/w/+L/5//7//n//v/z/9T/2//S/9r//P/f/9b/9v/i/+T/AADd/+H/5f/T/+n/3//Y/9n/7//2/9r/0P/W/+T/1P/Z/+3/6//n/+H/3v/v//X/8//w/+H/5//o/+j/8P/h/+X/7v/X/+X/9P/n/+X/4P/q//f/7v/e/+r/7v/d/+//6//i//H/7v/6//H/4v/j/+f/8//j/+H/6//1//T/2f/v//r/2//o//D/5//0//H/4v/y/+3/4P/a/93//P/z/+P/7P/s//L/9//c/97/+P/x/+T/4v/2/+3/5f/w//X/AADi/+n/+P/Z/97//v/+/+3/5//t/wEA8f/h/+v/5v/q/+z/AAA=\" type=\"audio/wav\" />\n",
+       "                    Your browser does not support the audio element.\n",
+       "                </audio>\n",
+       "              "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.Audio object>"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x = pitch(X, sample_rate)\n",
+    "plot_time_series(x)\n",
+    "ipd.Audio(x, rate=sample_rate)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|████████████████████████████████████████████████████████████████████████████████| 400/400 [00:16<00:00, 24.20it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Data Making Method 1\n",
+    "\n",
+    "syn_data1 = pd.DataFrame(columns=['feature', 'label'])\n",
+    "for i in tqdm(range(len(data2_df))):\n",
+    "    X, sample_rate = librosa.load(data2_df.path[i], res_type='kaiser_fast',duration=input_duration,sr=22050*2,offset=0.5)\n",
+    "    if data2_df.label[i]:\n",
+    "#     if data2_df.label[i] == \"male_positive\":\n",
+    "        X = noise(X)\n",
+    "        sample_rate = np.array(sample_rate)\n",
+    "        mfccs = np.mean(librosa.feature.mfcc(y=X, sr=sample_rate, n_mfcc=13), axis=0)\n",
+    "        feature = mfccs\n",
+    "        a = random.uniform(0, 1)\n",
+    "        syn_data1.loc[i] = [feature, data2_df.label[i]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|████████████████████████████████████████████████████████████████████████████████| 400/400 [01:13<00:00,  5.45it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Data Making Method 2\n",
+    "\n",
+    "syn_data2 = pd.DataFrame(columns=['feature', 'label'])\n",
+    "for i in tqdm(range(len(data2_df))):\n",
+    "    X, sample_rate = librosa.load(data2_df.path[i], res_type='kaiser_fast',duration=input_duration,sr=22050*2,offset=0.5)\n",
+    "    if data2_df.label[i]:\n",
+    "#     if data2_df.label[i] == \"male_positive\":\n",
+    "        X = pitch(X, sample_rate)\n",
+    "        sample_rate = np.array(sample_rate)\n",
+    "        mfccs = np.mean(librosa.feature.mfcc(y=X, sr=sample_rate, n_mfcc=13), axis=0)\n",
+    "        feature = mfccs\n",
+    "        a = random.uniform(0, 1)\n",
+    "        syn_data2.loc[i] = [feature, data2_df.label[i]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(400, 400)"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(syn_data1), len(syn_data2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "syn_data1 = syn_data1.reset_index(drop=True)\n",
+    "syn_data2 = syn_data2.reset_index(drop=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "400"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df4 = pd.DataFrame(syn_data1['feature'].values.tolist())\n",
+    "labels4 = syn_data1.label\n",
+    "syndf1 = pd.concat([df4,labels4], axis=1)\n",
+    "syndf1 = syndf1.rename(index=str, columns={\"0\": \"label\"})\n",
+    "syndf1 = syndf1.fillna(0)\n",
+    "len(syndf1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "      <th>2</th>\n",
+       "      <th>3</th>\n",
+       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <th>6</th>\n",
+       "      <th>7</th>\n",
+       "      <th>8</th>\n",
+       "      <th>9</th>\n",
+       "      <th>...</th>\n",
+       "      <th>250</th>\n",
+       "      <th>251</th>\n",
+       "      <th>252</th>\n",
+       "      <th>253</th>\n",
+       "      <th>254</th>\n",
+       "      <th>255</th>\n",
+       "      <th>256</th>\n",
+       "      <th>257</th>\n",
+       "      <th>258</th>\n",
+       "      <th>label</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-64.855751</td>\n",
+       "      <td>-63.358871</td>\n",
+       "      <td>-63.393188</td>\n",
+       "      <td>-65.198982</td>\n",
+       "      <td>-66.844467</td>\n",
+       "      <td>-65.800514</td>\n",
+       "      <td>-65.148788</td>\n",
+       "      <td>-66.985580</td>\n",
+       "      <td>-67.983994</td>\n",
+       "      <td>-67.379959</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-66.215157</td>\n",
+       "      <td>-65.396507</td>\n",
+       "      <td>-64.929726</td>\n",
+       "      <td>-65.205772</td>\n",
+       "      <td>-65.644073</td>\n",
+       "      <td>-66.384148</td>\n",
+       "      <td>-67.311501</td>\n",
+       "      <td>-67.854996</td>\n",
+       "      <td>-66.816277</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-57.958111</td>\n",
+       "      <td>-58.406982</td>\n",
+       "      <td>-55.038391</td>\n",
+       "      <td>-53.778809</td>\n",
+       "      <td>-55.958847</td>\n",
+       "      <td>-57.991249</td>\n",
+       "      <td>-54.842995</td>\n",
+       "      <td>-56.351154</td>\n",
+       "      <td>-58.587727</td>\n",
+       "      <td>-57.793148</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-56.560715</td>\n",
+       "      <td>-57.023724</td>\n",
+       "      <td>-55.504032</td>\n",
+       "      <td>-56.040653</td>\n",
+       "      <td>-56.615543</td>\n",
+       "      <td>-54.764996</td>\n",
+       "      <td>-54.789474</td>\n",
+       "      <td>-55.537930</td>\n",
+       "      <td>-56.321476</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>-57.883297</td>\n",
+       "      <td>-55.532600</td>\n",
+       "      <td>-55.683163</td>\n",
+       "      <td>-55.082191</td>\n",
+       "      <td>-54.591518</td>\n",
+       "      <td>-55.252483</td>\n",
+       "      <td>-56.320541</td>\n",
+       "      <td>-58.194515</td>\n",
+       "      <td>-55.806255</td>\n",
+       "      <td>-55.033134</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-54.362530</td>\n",
+       "      <td>-53.847050</td>\n",
+       "      <td>-55.437923</td>\n",
+       "      <td>-55.290115</td>\n",
+       "      <td>-54.340103</td>\n",
+       "      <td>-54.392666</td>\n",
+       "      <td>-52.920208</td>\n",
+       "      <td>-52.584892</td>\n",
+       "      <td>-54.723320</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-54.800858</td>\n",
+       "      <td>-53.834721</td>\n",
+       "      <td>-53.445721</td>\n",
+       "      <td>-54.077904</td>\n",
+       "      <td>-52.768120</td>\n",
+       "      <td>-52.694271</td>\n",
+       "      <td>-53.509712</td>\n",
+       "      <td>-53.141254</td>\n",
+       "      <td>-51.758213</td>\n",
+       "      <td>-53.617535</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-51.175571</td>\n",
+       "      <td>-52.345291</td>\n",
+       "      <td>-52.491051</td>\n",
+       "      <td>-51.029686</td>\n",
+       "      <td>-51.427402</td>\n",
+       "      <td>-53.667316</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-63.512199</td>\n",
+       "      <td>-61.168137</td>\n",
+       "      <td>-58.139809</td>\n",
+       "      <td>-58.403591</td>\n",
+       "      <td>-59.401348</td>\n",
+       "      <td>-60.404434</td>\n",
+       "      <td>-60.886902</td>\n",
+       "      <td>-60.672485</td>\n",
+       "      <td>-61.754280</td>\n",
+       "      <td>-63.086735</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-62.411758</td>\n",
+       "      <td>-62.060776</td>\n",
+       "      <td>-60.482826</td>\n",
+       "      <td>-60.156925</td>\n",
+       "      <td>-60.315922</td>\n",
+       "      <td>-59.152885</td>\n",
+       "      <td>-59.866859</td>\n",
+       "      <td>-62.615547</td>\n",
+       "      <td>-61.735577</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 260 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           0          1          2          3          4          5  \\\n",
+       "0 -64.855751 -63.358871 -63.393188 -65.198982 -66.844467 -65.800514   \n",
+       "1 -57.958111 -58.406982 -55.038391 -53.778809 -55.958847 -57.991249   \n",
+       "2 -57.883297 -55.532600 -55.683163 -55.082191 -54.591518 -55.252483   \n",
+       "3 -54.800858 -53.834721 -53.445721 -54.077904 -52.768120 -52.694271   \n",
+       "4 -63.512199 -61.168137 -58.139809 -58.403591 -59.401348 -60.404434   \n",
+       "\n",
+       "           6          7          8          9  ...        250        251  \\\n",
+       "0 -65.148788 -66.985580 -67.983994 -67.379959  ... -66.215157 -65.396507   \n",
+       "1 -54.842995 -56.351154 -58.587727 -57.793148  ... -56.560715 -57.023724   \n",
+       "2 -56.320541 -58.194515 -55.806255 -55.033134  ... -54.362530 -53.847050   \n",
+       "3 -53.509712 -53.141254 -51.758213 -53.617535  ... -51.175571 -52.345291   \n",
+       "4 -60.886902 -60.672485 -61.754280 -63.086735  ... -62.411758 -62.060776   \n",
+       "\n",
+       "         252        253        254        255        256        257  \\\n",
+       "0 -64.929726 -65.205772 -65.644073 -66.384148 -67.311501 -67.854996   \n",
+       "1 -55.504032 -56.040653 -56.615543 -54.764996 -54.789474 -55.537930   \n",
+       "2 -55.437923 -55.290115 -54.340103 -54.392666 -52.920208 -52.584892   \n",
+       "3 -52.491051 -51.029686 -51.427402 -53.667316   0.000000   0.000000   \n",
+       "4 -60.482826 -60.156925 -60.315922 -59.152885 -59.866859 -62.615547   \n",
+       "\n",
+       "         258      label  \n",
+       "0 -66.816277  male_calm  \n",
+       "1 -56.321476  male_calm  \n",
+       "2 -54.723320  male_calm  \n",
+       "3   0.000000  male_calm  \n",
+       "4 -61.735577  male_calm  \n",
+       "\n",
+       "[5 rows x 260 columns]"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "syndf1.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "400"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df4 = pd.DataFrame(syn_data2['feature'].values.tolist())\n",
+    "labels4 = syn_data2.label\n",
+    "syndf2 = pd.concat([df4,labels4], axis=1)\n",
+    "syndf2 = syndf2.rename(index=str, columns={\"0\": \"label\"})\n",
+    "syndf2 = syndf2.fillna(0)\n",
+    "len(syndf2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
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+       "      <th>2</th>\n",
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+       "      <th>7</th>\n",
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+       "      <th>252</th>\n",
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+       "      <th>254</th>\n",
+       "      <th>255</th>\n",
+       "      <th>256</th>\n",
+       "      <th>257</th>\n",
+       "      <th>258</th>\n",
+       "      <th>label</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.151138</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>-71.179558</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-67.196854</td>\n",
+       "      <td>-68.388657</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.532127</td>\n",
+       "      <td>-68.461342</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>-69.705093</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.428093</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>-69.740433</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-68.112289</td>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>-69.590317</td>\n",
+       "      <td>-69.782700</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.599648</td>\n",
+       "      <td>-74.808784</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>-74.858246</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 260 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           0          1          2          3          4          5  \\\n",
+       "0 -71.179558 -71.179558 -71.179558 -71.179558 -71.179558 -71.179558   \n",
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+       "4 -74.858246 -74.858246 -74.858246 -74.858246 -74.858246 -74.858246   \n",
+       "\n",
+       "           6          7          8          9  ...        250        251  \\\n",
+       "0 -71.179558 -71.179558 -71.179558 -71.179558  ... -71.179558 -71.179558   \n",
+       "1 -67.196854 -68.388657 -68.532127 -68.532127  ... -68.532127 -68.532127   \n",
+       "2 -69.740433 -69.740433 -69.740433 -69.428093  ... -69.740433 -69.740433   \n",
+       "3 -69.782700 -69.782700 -69.782700 -69.782700  ... -68.112289 -69.782700   \n",
+       "4 -74.858246 -74.599648 -74.808784 -74.858246  ... -74.858246 -74.858246   \n",
+       "\n",
+       "         252        253        254        255        256        257  \\\n",
+       "0 -71.179558 -71.151138 -71.179558 -71.179558 -71.179558 -71.179558   \n",
+       "1 -68.532127 -68.532127 -68.532127 -68.532127 -68.532127 -68.532127   \n",
+       "2 -69.740433 -69.740433 -69.740433 -69.740433 -69.740433 -69.740433   \n",
+       "3 -69.782700 -69.782700 -69.590317 -69.782700   0.000000   0.000000   \n",
+       "4 -74.858246 -74.858246 -74.858246 -74.858246 -74.858246 -74.858246   \n",
+       "\n",
+       "         258      label  \n",
+       "0 -71.179558  male_calm  \n",
+       "1 -68.461342  male_calm  \n",
+       "2 -69.740433  male_calm  \n",
+       "3   0.000000  male_calm  \n",
+       "4 -74.858246  male_calm  \n",
+       "\n",
+       "[5 rows x 260 columns]"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "syndf2.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "    <tr>\n",
+       "      <th>0</th>\n",
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+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-69.957710</td>\n",
+       "      <td>-68.377602</td>\n",
+       "      <td>-69.862564</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>-70.122139</td>\n",
+       "      <td>-68.554955</td>\n",
+       "      <td>-70.206528</td>\n",
+       "      <td>-70.267769</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-65.239815</td>\n",
+       "      <td>-65.536194</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>-67.126572</td>\n",
+       "      <td>-67.557388</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>-69.673286</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.620773</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-68.906570</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.383514</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>-69.693306</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-68.754860</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-68.359085</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-68.552094</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>-68.688614</td>\n",
+       "      <td>-69.051399</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.719650</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.303635</td>\n",
+       "      <td>-72.806808</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>-73.841370</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 260 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           0          1          2          3          4          5  \\\n",
+       "0 -70.267769 -70.267769 -70.267769 -70.267769 -70.267769 -70.267769   \n",
+       "1 -67.557388 -67.557388 -67.557388 -67.557388 -67.557388 -67.557388   \n",
+       "2 -69.673286 -69.693306 -69.693306 -69.693306 -69.693306 -69.693306   \n",
+       "3 -69.051399 -69.051399 -69.051399 -69.051399 -69.051399 -68.754860   \n",
+       "4 -73.841370 -73.841370 -73.841370 -73.719650 -73.841370 -73.841370   \n",
+       "\n",
+       "           6          7          8          9  ...        250        251  \\\n",
+       "0 -70.267769 -70.267769 -70.267769 -70.267769  ... -70.267769 -69.957710   \n",
+       "1 -65.239815 -65.536194 -67.557388 -67.557388  ... -67.557388 -67.557388   \n",
+       "2 -69.693306 -69.620773 -69.693306 -68.906570  ... -69.693306 -69.693306   \n",
+       "3 -69.051399 -69.051399 -69.051399 -68.359085  ... -68.552094 -69.051399   \n",
+       "4 -73.841370 -73.303635 -72.806808 -73.841370  ... -73.841370 -73.841370   \n",
+       "\n",
+       "         252        253        254        255        256        257  \\\n",
+       "0 -68.377602 -69.862564 -70.267769 -70.122139 -68.554955 -70.206528   \n",
+       "1 -67.557388 -67.557388 -67.557388 -67.557388 -67.557388 -67.126572   \n",
+       "2 -69.693306 -69.693306 -69.383514 -69.693306 -69.693306 -69.693306   \n",
+       "3 -69.051399 -69.051399 -68.688614 -69.051399   0.000000   0.000000   \n",
+       "4 -73.841370 -73.841370 -73.841370 -73.841370 -73.841370 -73.841370   \n",
+       "\n",
+       "         258      label  \n",
+       "0 -70.267769  male_calm  \n",
+       "1 -67.557388  male_calm  \n",
+       "2 -69.693306  male_calm  \n",
+       "3   0.000000  male_calm  \n",
+       "4 -73.841370  male_calm  \n",
+       "\n",
+       "[5 rows x 260 columns]"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Combining the Proccessed data with original\n",
+    "combined_df = pd.concat([rnewdf, syndf1, syndf2], ignore_index=True)\n",
+    "combined_df = combined_df.fillna(0)\n",
+    "combined_df.head()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#  Stratified Shuffle Split\n",
+    "from sklearn.model_selection import StratifiedShuffleSplit\n",
+    "X = combined_df.drop(['label'], axis=1)\n",
+    "y = combined_df.label\n",
+    "xxx = StratifiedShuffleSplit(1, test_size=0.2, random_state=12)\n",
+    "for train_index, test_index in xxx.split(X, y):\n",
+    "    X_train, X_test = X.iloc[train_index], X.iloc[test_index]\n",
+    "    y_train, y_test = y.iloc[train_index], y.iloc[test_index]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "male_sad        192\n",
+       "male_happy      192\n",
+       "male_angry      192\n",
+       "male_fearful    192\n",
+       "male_calm       192\n",
+       "Name: label, dtype: int64"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y_train.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "male_sad        48\n",
+       "male_angry      48\n",
+       "male_fearful    48\n",
+       "male_calm       48\n",
+       "male_happy      48\n",
+       "Name: label, dtype: int64"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y_test.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_train = np.array(X_train)\n",
+    "y_train = np.array(y_train)\n",
+    "X_test = np.array(X_test)\n",
+    "y_test = np.array(y_test)\n",
+    "lb = LabelEncoder()\n",
+    "y_train = np_utils.to_categorical(lb.fit_transform(y_train))\n",
+    "y_test = np_utils.to_categorical(lb.fit_transform(y_test))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0., 0., 1., 0., 0.],\n",
+       "       [0., 0., 1., 0., 0.],\n",
+       "       [0., 0., 0., 0., 1.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., 0., 1.],\n",
+       "       [0., 0., 0., 1., 0.],\n",
+       "       [0., 1., 0., 0., 0.]], dtype=float32)"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[-42.93526077, -39.98469925, -37.94607544, ...,   0.        ,\n",
+       "          0.        ,   0.        ],\n",
+       "       [-41.03386688, -43.47372818, -44.57199478, ...,   0.        ,\n",
+       "          0.        ,   0.        ],\n",
+       "       [-56.74127579, -57.09694672, -60.33541107, ..., -58.06520081,\n",
+       "        -64.63926697, -68.11162567],\n",
+       "       ...,\n",
+       "       [-52.57389069, -51.16184998, -52.06274033, ...,   0.        ,\n",
+       "          0.        ,   0.        ],\n",
+       "       [-53.63426971, -49.37136459, -47.1566391 , ...,   0.        ,\n",
+       "          0.        ,   0.        ],\n",
+       "       [-47.53664017, -48.37870407, -49.47584915, ..., -59.47858047,\n",
+       "        -60.6610527 , -57.66851044]])"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(960, 259)"
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_train.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Creating the CNN Model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_traincnn = np.expand_dims(X_train, axis=2)\n",
+    "x_testcnn = np.expand_dims(X_test, axis=2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Set up Keras util functions\n",
+    "\n",
+    "from keras import backend as K\n",
+    "\n",
+    "def precision(y_true, y_pred):\n",
+    "    true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n",
+    "    predicted_positives = K.sum(K.round(K.clip(y_pred, 0, 1)))\n",
+    "    precision = true_positives / (predicted_positives + K.epsilon())\n",
+    "    return precision\n",
+    "\n",
+    "\n",
+    "def recall(y_true, y_pred):\n",
+    "    true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n",
+    "    possible_positives = K.sum(K.round(K.clip(y_true, 0, 1)))\n",
+    "    recall = true_positives / (possible_positives + K.epsilon())\n",
+    "    return recall\n",
+    "\n",
+    "\n",
+    "def fscore(y_true, y_pred):\n",
+    "    if K.sum(K.round(K.clip(y_true, 0, 1))) == 0:\n",
+    "        return 0\n",
+    "\n",
+    "    p = precision(y_true, y_pred)\n",
+    "    r = recall(y_true, y_pred)\n",
+    "    f_score = 2 * (p * r) / (p + r + K.epsilon())\n",
+    "    return f_score\n",
+    "\n",
+    "def get_lr_metric(optimizer):\n",
+    "    def lr(y_true, y_pred):\n",
+    "        return optimizer.lr\n",
+    "    return lr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# New model\n",
+    "model = Sequential()\n",
+    "model.add(Conv1D(256, 8, padding='valid',input_shape=(X_train.shape[1],1)))\n",
+    "model.add(Activation('relu'))\n",
+    "model.add(Conv1D(256, 8, padding='same'))\n",
+    "model.add(BatchNormalization())\n",
+    "model.add(Activation('relu'))\n",
+    "model.add(Dropout(0.25))\n",
+    "model.add(MaxPooling1D(pool_size=(8)))\n",
+    "model.add(Conv1D(128, 8, padding='same'))\n",
+    "model.add(Activation('relu'))\n",
+    "model.add(Conv1D(128, 8, padding='same'))\n",
+    "model.add(Activation('relu'))\n",
+    "model.add(Conv1D(128, 8, padding='same'))\n",
+    "model.add(Activation('relu'))\n",
+    "model.add(Conv1D(128, 8, padding='same'))\n",
+    "model.add(BatchNormalization())\n",
+    "model.add(Activation('relu'))\n",
+    "model.add(Dropout(0.25))\n",
+    "model.add(MaxPooling1D(pool_size=(8)))\n",
+    "model.add(Conv1D(64, 8, padding='same'))\n",
+    "model.add(Activation('relu'))\n",
+    "model.add(Conv1D(64, 8, padding='same'))\n",
+    "model.add(Activation('relu'))\n",
+    "model.add(Flatten())\n",
+    "# Edit according to target class no.\n",
+    "model.add(Dense(5))\n",
+    "model.add(Activation('softmax'))\n",
+    "#opt = keras.optimizers.SGD(lr=0.0001, momentum=0.0, decay=0.0, nesterov=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Model: \"sequential_1\"\n",
+      "_________________________________________________________________\n",
+      "Layer (type)                 Output Shape              Param #   \n",
+      "=================================================================\n",
+      "conv1d_8 (Conv1D)            (None, 252, 256)          2304      \n",
+      "_________________________________________________________________\n",
+      "activation_9 (Activation)    (None, 252, 256)          0         \n",
+      "_________________________________________________________________\n",
+      "conv1d_9 (Conv1D)            (None, 252, 256)          524544    \n",
+      "_________________________________________________________________\n",
+      "batch_normalization_2 (Batch (None, 252, 256)          1024      \n",
+      "_________________________________________________________________\n",
+      "activation_10 (Activation)   (None, 252, 256)          0         \n",
+      "_________________________________________________________________\n",
+      "dropout_2 (Dropout)          (None, 252, 256)          0         \n",
+      "_________________________________________________________________\n",
+      "max_pooling1d_2 (MaxPooling1 (None, 31, 256)           0         \n",
+      "_________________________________________________________________\n",
+      "conv1d_10 (Conv1D)           (None, 31, 128)           262272    \n",
+      "_________________________________________________________________\n",
+      "activation_11 (Activation)   (None, 31, 128)           0         \n",
+      "_________________________________________________________________\n",
+      "conv1d_11 (Conv1D)           (None, 31, 128)           131200    \n",
+      "_________________________________________________________________\n",
+      "activation_12 (Activation)   (None, 31, 128)           0         \n",
+      "_________________________________________________________________\n",
+      "conv1d_12 (Conv1D)           (None, 31, 128)           131200    \n",
+      "_________________________________________________________________\n",
+      "activation_13 (Activation)   (None, 31, 128)           0         \n",
+      "_________________________________________________________________\n",
+      "conv1d_13 (Conv1D)           (None, 31, 128)           131200    \n",
+      "_________________________________________________________________\n",
+      "batch_normalization_3 (Batch (None, 31, 128)           512       \n",
+      "_________________________________________________________________\n",
+      "activation_14 (Activation)   (None, 31, 128)           0         \n",
+      "_________________________________________________________________\n",
+      "dropout_3 (Dropout)          (None, 31, 128)           0         \n",
+      "_________________________________________________________________\n",
+      "max_pooling1d_3 (MaxPooling1 (None, 3, 128)            0         \n",
+      "_________________________________________________________________\n",
+      "conv1d_14 (Conv1D)           (None, 3, 64)             65600     \n",
+      "_________________________________________________________________\n",
+      "activation_15 (Activation)   (None, 3, 64)             0         \n",
+      "_________________________________________________________________\n",
+      "conv1d_15 (Conv1D)           (None, 3, 64)             32832     \n",
+      "_________________________________________________________________\n",
+      "activation_16 (Activation)   (None, 3, 64)             0         \n",
+      "_________________________________________________________________\n",
+      "flatten_1 (Flatten)          (None, 192)               0         \n",
+      "_________________________________________________________________\n",
+      "dense_1 (Dense)              (None, 5)                 965       \n",
+      "_________________________________________________________________\n",
+      "activation_17 (Activation)   (None, 5)                 0         \n",
+      "=================================================================\n",
+      "Total params: 1,283,653\n",
+      "Trainable params: 1,282,885\n",
+      "Non-trainable params: 768\n",
+      "_________________________________________________________________\n"
+     ]
+    }
+   ],
+   "source": [
+    "model.summary()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Compile your model\n",
+    "model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Train on 960 samples, validate on 240 samples\n",
+      "Epoch 1/100\n",
+      "960/960 [==============================] - 6s 6ms/sample - loss: 1.4362 - accuracy: 0.3729 - val_loss: 2.7278 - val_accuracy: 0.2333\n",
+      "Epoch 2/100\n",
+      "960/960 [==============================] - 1s 1ms/sample - loss: 1.3393 - accuracy: 0.4292 - val_loss: 1.7512 - val_accuracy: 0.3333\n",
+      "Epoch 3/100\n",
+      "960/960 [==============================] - 1s 1ms/sample - loss: 1.2899 - accuracy: 0.4583 - val_loss: 1.6033 - val_accuracy: 0.4000\n",
+      "Epoch 4/100\n",
+      "960/960 [==============================] - 1s 1ms/sample - loss: 1.2624 - accuracy: 0.4885 - val_loss: 1.5686 - val_accuracy: 0.3708\n",
+      "Epoch 5/100\n",
+      "960/960 [==============================] - 1s 1ms/sample - loss: 1.2195 - accuracy: 0.5042 - val_loss: 1.3342 - val_accuracy: 0.4208\n",
+      "Epoch 6/100\n",
+      "960/960 [==============================] - 1s 724us/sample - loss: 1.2136 - accuracy: 0.5104 - val_loss: 1.6374 - val_accuracy: 0.3625\n",
+      "Epoch 7/100\n",
+      "960/960 [==============================] - 1s 729us/sample - loss: 1.1253 - accuracy: 0.5490 - val_loss: 1.6155 - val_accuracy: 0.3958\n",
+      "Epoch 8/100\n",
+      "960/960 [==============================] - 1s 713us/sample - loss: 1.1162 - accuracy: 0.5448 - val_loss: 1.3668 - val_accuracy: 0.3875\n",
+      "Epoch 9/100\n",
+      "960/960 [==============================] - 1s 710us/sample - loss: 1.0643 - accuracy: 0.5813 - val_loss: 3.3321 - val_accuracy: 0.3000\n",
+      "Epoch 10/100\n",
+      "960/960 [==============================] - 1s 732us/sample - loss: 1.0636 - accuracy: 0.5719 - val_loss: 1.4826 - val_accuracy: 0.4292\n",
+      "Epoch 11/100\n",
+      "960/960 [==============================] - 1s 747us/sample - loss: 0.9981 - accuracy: 0.6073 - val_loss: 1.9360 - val_accuracy: 0.3208\n",
+      "Epoch 12/100\n",
+      "960/960 [==============================] - 1s 738us/sample - loss: 0.9453 - accuracy: 0.6250 - val_loss: 2.5081 - val_accuracy: 0.2458\n",
+      "Epoch 13/100\n",
+      "960/960 [==============================] - 1s 737us/sample - loss: 0.9483 - accuracy: 0.6323 - val_loss: 1.6414 - val_accuracy: 0.4208\n",
+      "Epoch 14/100\n",
+      "960/960 [==============================] - 1s 728us/sample - loss: 0.8691 - accuracy: 0.6458 - val_loss: 1.9625 - val_accuracy: 0.3250\n",
+      "Epoch 15/100\n",
+      "960/960 [==============================] - 1s 1ms/sample - loss: 0.8456 - accuracy: 0.6781 - val_loss: 1.0845 - val_accuracy: 0.5667\n",
+      "Epoch 16/100\n",
+      "960/960 [==============================] - 1s 744us/sample - loss: 0.8223 - accuracy: 0.6802 - val_loss: 1.6783 - val_accuracy: 0.4458\n",
+      "Epoch 17/100\n",
+      "960/960 [==============================] - 1s 730us/sample - loss: 0.7375 - accuracy: 0.7083 - val_loss: 1.2490 - val_accuracy: 0.5375\n",
+      "Epoch 18/100\n",
+      "960/960 [==============================] - 1s 745us/sample - loss: 0.7139 - accuracy: 0.7271 - val_loss: 1.8571 - val_accuracy: 0.3792\n",
+      "Epoch 19/100\n",
+      "960/960 [==============================] - 1s 1ms/sample - loss: 0.7666 - accuracy: 0.7042 - val_loss: 0.9645 - val_accuracy: 0.6333\n",
+      "Epoch 20/100\n",
+      "960/960 [==============================] - 1s 848us/sample - loss: 0.6670 - accuracy: 0.7458 - val_loss: 1.2328 - val_accuracy: 0.5417\n",
+      "Epoch 21/100\n",
+      "960/960 [==============================] - 1s 726us/sample - loss: 0.5327 - accuracy: 0.8010 - val_loss: 1.4042 - val_accuracy: 0.4458\n",
+      "Epoch 22/100\n",
+      "960/960 [==============================] - 1s 788us/sample - loss: 0.5466 - accuracy: 0.7990 - val_loss: 1.2005 - val_accuracy: 0.5500\n",
+      "Epoch 23/100\n",
+      "960/960 [==============================] - 1s 743us/sample - loss: 0.4691 - accuracy: 0.8323 - val_loss: 1.3384 - val_accuracy: 0.5250\n",
+      "Epoch 24/100\n",
+      "960/960 [==============================] - 1s 721us/sample - loss: 0.4758 - accuracy: 0.8313 - val_loss: 1.2724 - val_accuracy: 0.5250\n",
+      "Epoch 25/100\n",
+      "960/960 [==============================] - 1s 746us/sample - loss: 0.4957 - accuracy: 0.8010 - val_loss: 1.0410 - val_accuracy: 0.6167\n",
+      "Epoch 26/100\n",
+      "960/960 [==============================] - 1s 745us/sample - loss: 0.4511 - accuracy: 0.8292 - val_loss: 1.9496 - val_accuracy: 0.4333\n",
+      "Epoch 27/100\n",
+      "960/960 [==============================] - 1s 735us/sample - loss: 0.4443 - accuracy: 0.8240 - val_loss: 1.6557 - val_accuracy: 0.3917\n",
+      "Epoch 28/100\n",
+      "960/960 [==============================] - 1s 791us/sample - loss: 0.4067 - accuracy: 0.8448 - val_loss: 1.7252 - val_accuracy: 0.4917\n",
+      "Epoch 29/100\n",
+      "960/960 [==============================] - 1s 732us/sample - loss: 0.2885 - accuracy: 0.8865 - val_loss: 1.7441 - val_accuracy: 0.4750\n",
+      "Epoch 30/100\n",
+      "960/960 [==============================] - 1s 736us/sample - loss: 0.2764 - accuracy: 0.9031 - val_loss: 1.3401 - val_accuracy: 0.5042\n",
+      "Epoch 31/100\n",
+      "960/960 [==============================] - 1s 730us/sample - loss: 0.2253 - accuracy: 0.9125 - val_loss: 1.4147 - val_accuracy: 0.5583\n",
+      "Epoch 32/100\n",
+      "960/960 [==============================] - 1s 729us/sample - loss: 0.2505 - accuracy: 0.9208 - val_loss: 1.5786 - val_accuracy: 0.4750\n",
+      "Epoch 33/100\n",
+      "960/960 [==============================] - 1s 817us/sample - loss: 0.2637 - accuracy: 0.9062 - val_loss: 1.9482 - val_accuracy: 0.4417\n",
+      "Epoch 34/100\n",
+      "960/960 [==============================] - ETA: 0s - loss: 0.2530 - accuracy: 0.91 - 1s 745us/sample - loss: 0.2546 - accuracy: 0.9115 - val_loss: 1.0924 - val_accuracy: 0.6542\n",
+      "Epoch 35/100\n",
+      "960/960 [==============================] - 1s 746us/sample - loss: 0.2242 - accuracy: 0.9177 - val_loss: 1.0364 - val_accuracy: 0.6583\n",
+      "Epoch 36/100\n",
+      "960/960 [==============================] - 1s 731us/sample - loss: 0.1854 - accuracy: 0.9260 - val_loss: 1.2674 - val_accuracy: 0.6500\n",
+      "Epoch 37/100\n",
+      "960/960 [==============================] - 1s 957us/sample - loss: 0.1553 - accuracy: 0.9469 - val_loss: 0.9580 - val_accuracy: 0.6458\n",
+      "Epoch 38/100\n",
+      "960/960 [==============================] - 1s 738us/sample - loss: 0.1060 - accuracy: 0.9573 - val_loss: 1.4276 - val_accuracy: 0.5583\n",
+      "Epoch 39/100\n",
+      "960/960 [==============================] - 1s 731us/sample - loss: 0.1058 - accuracy: 0.9625 - val_loss: 1.0530 - val_accuracy: 0.6792\n",
+      "Epoch 40/100\n",
+      "960/960 [==============================] - 1s 737us/sample - loss: 0.0946 - accuracy: 0.9708 - val_loss: 1.0101 - val_accuracy: 0.6875\n",
+      "Epoch 41/100\n",
+      "960/960 [==============================] - 1s 1ms/sample - loss: 0.1063 - accuracy: 0.9635 - val_loss: 0.8187 - val_accuracy: 0.7208\n",
+      "Epoch 42/100\n",
+      "960/960 [==============================] - 1s 750us/sample - loss: 0.0978 - accuracy: 0.9656 - val_loss: 1.1778 - val_accuracy: 0.6583\n",
+      "Epoch 43/100\n",
+      "960/960 [==============================] - 1s 741us/sample - loss: 0.1260 - accuracy: 0.9542 - val_loss: 0.9374 - val_accuracy: 0.7292\n",
+      "Epoch 44/100\n",
+      "960/960 [==============================] - 1s 725us/sample - loss: 0.1634 - accuracy: 0.9438 - val_loss: 1.4342 - val_accuracy: 0.6083\n",
+      "Epoch 45/100\n",
+      "960/960 [==============================] - 1s 1ms/sample - loss: 0.1027 - accuracy: 0.9677 - val_loss: 0.7154 - val_accuracy: 0.7750\n",
+      "Epoch 46/100\n",
+      "960/960 [==============================] - 1s 813us/sample - loss: 0.1195 - accuracy: 0.9604 - val_loss: 1.4890 - val_accuracy: 0.5917\n",
+      "Epoch 47/100\n",
+      "960/960 [==============================] - 1s 730us/sample - loss: 0.1019 - accuracy: 0.9677 - val_loss: 1.1277 - val_accuracy: 0.6500\n",
+      "Epoch 48/100\n",
+      "960/960 [==============================] - 1s 990us/sample - loss: 0.0804 - accuracy: 0.9688 - val_loss: 0.6902 - val_accuracy: 0.7958\n",
+      "Epoch 49/100\n",
+      "960/960 [==============================] - 1s 764us/sample - loss: 0.1255 - accuracy: 0.9531 - val_loss: 0.7347 - val_accuracy: 0.7792\n",
+      "Epoch 50/100\n",
+      "960/960 [==============================] - 1s 817us/sample - loss: 0.0933 - accuracy: 0.9635 - val_loss: 0.8019 - val_accuracy: 0.7750\n",
+      "Epoch 51/100\n",
+      "960/960 [==============================] - 1s 731us/sample - loss: 0.0610 - accuracy: 0.9771 - val_loss: 0.9703 - val_accuracy: 0.7125\n",
+      "Epoch 52/100\n",
+      "960/960 [==============================] - 1s 744us/sample - loss: 0.0395 - accuracy: 0.9844 - val_loss: 0.9308 - val_accuracy: 0.7292\n",
+      "Epoch 53/100\n",
+      "960/960 [==============================] - 1s 729us/sample - loss: 0.0424 - accuracy: 0.9896 - val_loss: 0.7005 - val_accuracy: 0.7917\n",
+      "Epoch 54/100\n",
+      "960/960 [==============================] - 1s 737us/sample - loss: 0.0798 - accuracy: 0.9667 - val_loss: 1.7202 - val_accuracy: 0.5458\n",
+      "Epoch 55/100\n",
+      "960/960 [==============================] - 1s 738us/sample - loss: 0.1427 - accuracy: 0.9490 - val_loss: 0.7046 - val_accuracy: 0.7833\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 56/100\n",
+      "960/960 [==============================] - 1s 728us/sample - loss: 0.0999 - accuracy: 0.9635 - val_loss: 0.9488 - val_accuracy: 0.6917\n",
+      "Epoch 57/100\n",
+      "960/960 [==============================] - 1s 1ms/sample - loss: 0.0428 - accuracy: 0.9885 - val_loss: 0.5218 - val_accuracy: 0.8375\n",
+      "Epoch 58/100\n",
+      "960/960 [==============================] - 1s 1ms/sample - loss: 0.0089 - accuracy: 1.0000 - val_loss: 0.4007 - val_accuracy: 0.8708\n",
+      "Epoch 59/100\n",
+      "960/960 [==============================] - 1s 748us/sample - loss: 0.0039 - accuracy: 1.0000 - val_loss: 0.6088 - val_accuracy: 0.8167\n",
+      "Epoch 60/100\n",
+      "960/960 [==============================] - 1s 739us/sample - loss: 0.0111 - accuracy: 0.9969 - val_loss: 1.1007 - val_accuracy: 0.7042\n",
+      "Epoch 61/100\n",
+      "960/960 [==============================] - 1s 735us/sample - loss: 0.0125 - accuracy: 0.9969 - val_loss: 1.1661 - val_accuracy: 0.7000\n",
+      "Epoch 62/100\n",
+      "960/960 [==============================] - 1s 742us/sample - loss: 0.0136 - accuracy: 0.9937 - val_loss: 0.5030 - val_accuracy: 0.8417\n",
+      "Epoch 63/100\n",
+      "960/960 [==============================] - 1s 745us/sample - loss: 0.0339 - accuracy: 0.9833 - val_loss: 1.2877 - val_accuracy: 0.7000\n",
+      "Epoch 64/100\n",
+      "960/960 [==============================] - 1s 727us/sample - loss: 0.0376 - accuracy: 0.9906 - val_loss: 1.3381 - val_accuracy: 0.7083\n",
+      "Epoch 65/100\n",
+      "960/960 [==============================] - 1s 731us/sample - loss: 0.1065 - accuracy: 0.9667 - val_loss: 2.8029 - val_accuracy: 0.4500\n",
+      "Epoch 66/100\n",
+      "960/960 [==============================] - 1s 748us/sample - loss: 0.0921 - accuracy: 0.9719 - val_loss: 0.7000 - val_accuracy: 0.7708\n",
+      "Epoch 67/100\n",
+      "960/960 [==============================] - 1s 738us/sample - loss: 0.0460 - accuracy: 0.9854 - val_loss: 0.9953 - val_accuracy: 0.7250\n",
+      "Epoch 68/100\n",
+      "960/960 [==============================] - 1s 739us/sample - loss: 0.0310 - accuracy: 0.9865 - val_loss: 0.5849 - val_accuracy: 0.7792\n",
+      "Epoch 69/100\n",
+      "960/960 [==============================] - 1s 724us/sample - loss: 0.1190 - accuracy: 0.9646 - val_loss: 1.1394 - val_accuracy: 0.6958\n",
+      "Epoch 70/100\n",
+      "960/960 [==============================] - 1s 730us/sample - loss: 0.0738 - accuracy: 0.9708 - val_loss: 0.9056 - val_accuracy: 0.7250\n",
+      "Epoch 71/100\n",
+      "960/960 [==============================] - 1s 746us/sample - loss: 0.0609 - accuracy: 0.9802 - val_loss: 1.4468 - val_accuracy: 0.6458\n",
+      "Epoch 72/100\n",
+      "960/960 [==============================] - 1s 747us/sample - loss: 0.0537 - accuracy: 0.9823 - val_loss: 0.6665 - val_accuracy: 0.7542\n",
+      "Epoch 73/100\n",
+      "960/960 [==============================] - 1s 742us/sample - loss: 0.0261 - accuracy: 0.9927 - val_loss: 1.0665 - val_accuracy: 0.7500\n",
+      "Epoch 74/100\n",
+      "960/960 [==============================] - 1s 732us/sample - loss: 0.0212 - accuracy: 0.9969 - val_loss: 0.8447 - val_accuracy: 0.7625\n",
+      "Epoch 75/100\n",
+      "960/960 [==============================] - 1s 714us/sample - loss: 0.0302 - accuracy: 0.9875 - val_loss: 0.6991 - val_accuracy: 0.8042\n",
+      "Epoch 76/100\n",
+      "960/960 [==============================] - 1s 733us/sample - loss: 0.0941 - accuracy: 0.9771 - val_loss: 0.5386 - val_accuracy: 0.8167\n",
+      "Epoch 77/100\n",
+      "960/960 [==============================] - 1s 723us/sample - loss: 0.0508 - accuracy: 0.9802 - val_loss: 0.5119 - val_accuracy: 0.8292\n",
+      "Epoch 78/100\n",
+      "960/960 [==============================] - 1s 731us/sample - loss: 0.0171 - accuracy: 0.9948 - val_loss: 0.5234 - val_accuracy: 0.8667\n",
+      "Epoch 79/100\n",
+      "960/960 [==============================] - 1s 730us/sample - loss: 0.0074 - accuracy: 0.9979 - val_loss: 0.4686 - val_accuracy: 0.8833\n",
+      "Epoch 80/100\n",
+      "960/960 [==============================] - 1s 725us/sample - loss: 0.0040 - accuracy: 0.9990 - val_loss: 0.5319 - val_accuracy: 0.8542\n",
+      "Epoch 81/100\n",
+      "960/960 [==============================] - 1s 711us/sample - loss: 0.0019 - accuracy: 1.0000 - val_loss: 0.5223 - val_accuracy: 0.8625\n",
+      "Epoch 82/100\n",
+      "960/960 [==============================] - 1s 734us/sample - loss: 4.6260e-04 - accuracy: 1.0000 - val_loss: 0.5133 - val_accuracy: 0.8625\n",
+      "Epoch 83/100\n",
+      "960/960 [==============================] - 1s 728us/sample - loss: 0.0015 - accuracy: 1.0000 - val_loss: 0.5079 - val_accuracy: 0.8792\n",
+      "Epoch 84/100\n",
+      "960/960 [==============================] - 1s 728us/sample - loss: 6.4230e-04 - accuracy: 1.0000 - val_loss: 0.5095 - val_accuracy: 0.8792\n",
+      "Epoch 85/100\n",
+      "960/960 [==============================] - 1s 711us/sample - loss: 2.8968e-04 - accuracy: 1.0000 - val_loss: 0.5313 - val_accuracy: 0.8667\n",
+      "Epoch 86/100\n",
+      "960/960 [==============================] - 1s 738us/sample - loss: 5.4872e-04 - accuracy: 1.0000 - val_loss: 0.4956 - val_accuracy: 0.8708\n",
+      "Epoch 87/100\n",
+      "960/960 [==============================] - 1s 720us/sample - loss: 6.3170e-04 - accuracy: 1.0000 - val_loss: 0.4817 - val_accuracy: 0.8833\n",
+      "Epoch 88/100\n",
+      "960/960 [==============================] - 1s 730us/sample - loss: 0.0020 - accuracy: 0.9990 - val_loss: 0.5426 - val_accuracy: 0.8708\n",
+      "Epoch 89/100\n",
+      "960/960 [==============================] - 1s 729us/sample - loss: 0.0383 - accuracy: 0.9854 - val_loss: 2.3101 - val_accuracy: 0.5292\n",
+      "Epoch 90/100\n",
+      "960/960 [==============================] - 1s 726us/sample - loss: 0.1355 - accuracy: 0.9615 - val_loss: 1.1111 - val_accuracy: 0.6875\n",
+      "Epoch 91/100\n",
+      "960/960 [==============================] - 1s 732us/sample - loss: 0.0348 - accuracy: 0.9896 - val_loss: 0.8874 - val_accuracy: 0.7708\n",
+      "Epoch 92/100\n",
+      "960/960 [==============================] - 1s 749us/sample - loss: 0.0617 - accuracy: 0.9812 - val_loss: 0.9115 - val_accuracy: 0.7375\n",
+      "Epoch 93/100\n",
+      "960/960 [==============================] - 1s 746us/sample - loss: 0.0128 - accuracy: 0.9969 - val_loss: 0.7474 - val_accuracy: 0.8000\n",
+      "Epoch 94/100\n",
+      "960/960 [==============================] - 1s 742us/sample - loss: 0.0056 - accuracy: 1.0000 - val_loss: 0.6709 - val_accuracy: 0.8375\n",
+      "Epoch 95/100\n",
+      "960/960 [==============================] - 1s 737us/sample - loss: 0.0011 - accuracy: 1.0000 - val_loss: 0.6294 - val_accuracy: 0.8500\n",
+      "Epoch 96/100\n",
+      "960/960 [==============================] - 1s 721us/sample - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.5442 - val_accuracy: 0.8625\n",
+      "Epoch 97/100\n",
+      "960/960 [==============================] - 1s 812us/sample - loss: 0.0014 - accuracy: 1.0000 - val_loss: 0.4642 - val_accuracy: 0.8792\n",
+      "Epoch 98/100\n",
+      "960/960 [==============================] - 1s 717us/sample - loss: 0.0011 - accuracy: 1.0000 - val_loss: 0.5830 - val_accuracy: 0.8458\n",
+      "Epoch 99/100\n",
+      "960/960 [==============================] - 1s 740us/sample - loss: 8.2623e-04 - accuracy: 1.0000 - val_loss: 0.5310 - val_accuracy: 0.8583\n",
+      "Epoch 100/100\n",
+      "960/960 [==============================] - 1s 725us/sample - loss: 5.1894e-04 - accuracy: 1.0000 - val_loss: 0.5088 - val_accuracy: 0.8625\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Model Training\n",
+    "\n",
+    "lr_reduce = ReduceLROnPlateau(monitor='val_loss', factor=0.9, patience=20, min_lr=0.000001)\n",
+    "# Please change the model name accordingly.\n",
+    "mcp_save = ModelCheckpoint('E:\\\\8th sem\\\\Final_Year_Project_Files\\\\New Folder\\\\Data_noiseNshift.h5', save_best_only=True, monitor='val_loss', mode='min')\n",
+    "cnnhistory=model.fit(x_traincnn, y_train, batch_size=16, epochs=100,\n",
+    "                     validation_data=(x_testcnn, y_test), callbacks=[mcp_save, lr_reduce])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "# Plotting the Train Valid Loss Graph\n",
+    "\n",
+    "plt.plot(cnnhistory.history['loss'])\n",
+    "plt.plot(cnnhistory.history['val_loss'])\n",
+    "plt.title('model loss')\n",
+    "plt.ylabel('loss')\n",
+    "plt.xlabel('epoch')\n",
+    "plt.legend(['train', 'test'], loc='upper left')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Saving the model.json\n",
+    "\n",
+    "import json\n",
+    "model_json = model.to_json()\n",
+    "with open(\"E:\\\\8th sem\\\\Final_Year_Project_Files\\\\New Folder\\\\model.json\", \"w\") as json_file:\n",
+    "    json_file.write(model_json)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Loaded model from disk\n",
+      "accuracy: 87.08%\n"
+     ]
+    }
+   ],
+   "source": [
+    "import tensorflow as tf\n",
+    "from tensorflow.keras.initializers import glorot_uniform\n",
+    "loaded_model = tf.keras.models.load_model(\"E:\\\\8th sem\\\\Final_Year_Project_Files\\\\New Folder\\\\Data_noiseNshift.h5\",custom_objects={'GlorotUniform': glorot_uniform()})\n",
+    "print(\"Loaded model from disk\")\n",
+    " \n",
+    "# evaluate loaded model on test data\n",
+    "loaded_model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\n",
+    "score = loaded_model.evaluate(x_testcnn, y_test, verbose=0)\n",
+    "print(\"%s: %.2f%%\" % (loaded_model.metrics_names[1], score[1]*100))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Predicting emotions on the test data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "400"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(data2_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|████████████████████████████████████████████████████████████████████████████████| 400/400 [00:15<00:00, 25.91it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "data_test = pd.DataFrame(columns=['feature'])\n",
+    "for i in tqdm(range(len(data2_df))):\n",
+    "    X, sample_rate = librosa.load(data2_df.path[i], res_type='kaiser_fast',duration=input_duration,sr=22050*2,offset=0.5)\n",
+    "#     X = X[10000:90000]\n",
+    "    sample_rate = np.array(sample_rate)\n",
+    "    mfccs = np.mean(librosa.feature.mfcc(y=X, sr=sample_rate, n_mfcc=13), axis=0)\n",
+    "    feature = mfccs\n",
+    "    data_test.loc[i] = [feature]\n",
+    "    \n",
+    "test_valid = pd.DataFrame(data_test['feature'].values.tolist())\n",
+    "test_valid = np.array(test_valid)\n",
+    "test_valid_lb = np.array(data2_df.label)\n",
+    "lb = LabelEncoder()\n",
+    "test_valid_lb = np_utils.to_categorical(lb.fit_transform(test_valid_lb))\n",
+    "test_valid = np.expand_dims(test_valid, axis=2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "400/1 [================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================] - 0s 599us/sample\n"
+     ]
+    }
+   ],
+   "source": [
+    "preds = loaded_model.predict(test_valid, \n",
+    "                         batch_size=16, \n",
+    "                         verbose=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[1.0734923e-05, 9.9891412e-01, 3.3075224e-07, 2.9563749e-08,\n",
+       "        1.0748380e-03],\n",
+       "       [7.4007585e-05, 9.9838781e-01, 6.7539270e-07, 1.2393507e-05,\n",
+       "        1.5251203e-03],\n",
+       "       [5.1998140e-06, 9.9968588e-01, 1.2857044e-08, 3.1184527e-08,\n",
+       "        3.0885395e-04],\n",
+       "       ...,\n",
+       "       [4.5170836e-07, 2.6772174e-13, 9.9999952e-01, 1.2014882e-11,\n",
+       "        5.0442605e-08],\n",
+       "       [1.6392261e-07, 3.9528185e-12, 9.9999952e-01, 1.2567843e-09,\n",
+       "        3.1214594e-07],\n",
+       "       [2.3839435e-05, 1.1019921e-08, 9.9993277e-01, 2.6881271e-05,\n",
+       "        1.6423151e-05]], dtype=float32)"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "preds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preds1=preds.argmax(axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4,\n",
+       "       1, 4, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 2, 2, 3, 2, 2, 4, 1, 1, 1,\n",
+       "       1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0,\n",
+       "       0, 0, 0, 0, 0, 0, 2, 2, 2, 4, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1,\n",
+       "       3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0,\n",
+       "       0, 0, 2, 2, 4, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 4, 1, 1, 3, 3, 3, 3,\n",
+       "       3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2,\n",
+       "       2, 2, 2, 2, 2, 2, 1, 4, 1, 1, 4, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3,\n",
+       "       4, 4, 4, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 2, 4, 2, 2, 4, 2,\n",
+       "       2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 1,\n",
+       "       4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 4, 2, 2, 2, 2, 1, 1,\n",
+       "       4, 1, 3, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 1, 4,\n",
+       "       0, 0, 0, 0, 0, 0, 0, 0, 2, 4, 2, 3, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1,\n",
+       "       1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0,\n",
+       "       0, 0, 0, 0, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3,\n",
+       "       3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 0, 1, 0, 0, 0, 0, 0, 0,\n",
+       "       2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3,\n",
+       "       3, 3, 1, 4, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 2, 2,\n",
+       "       2, 2, 2, 2], dtype=int64)"
+      ]
+     },
+     "execution_count": 75,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "preds1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "abc = preds1.astype(int).flatten()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1 1 1 1 1 1 1 1 3 3 3 3 3 3 3 3 4 4 4 4 4 4 1 4 0 0 0 0 0 0 0 0 2 2 2 2 2\n",
+      " 3 2 2 4 1 1 1 1 1 1 1 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 0 0 0 0 0 0 0 0 2 2\n",
+      " 2 4 2 2 2 2 1 1 1 1 1 1 1 1 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 0 0 0 0 0 0 0\n",
+      " 0 2 2 4 2 2 2 2 2 1 1 1 1 1 4 1 1 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 0 0 0 0\n",
+      " 0 0 0 0 2 2 2 2 2 2 2 2 1 4 1 1 4 1 1 1 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 0\n",
+      " 0 0 0 0 0 0 0 2 4 2 2 4 2 2 2 1 1 1 1 1 1 1 1 3 3 3 3 3 3 3 3 4 4 4 1 4 4\n",
+      " 4 4 0 0 0 0 0 0 0 0 2 2 2 4 2 2 2 2 1 1 4 1 3 1 1 3 3 3 3 3 3 3 3 3 4 4 4\n",
+      " 4 4 4 1 4 0 0 0 0 0 0 0 0 2 4 2 3 2 2 2 2 1 1 1 1 1 1 1 1 3 3 3 3 3 3 3 3\n",
+      " 4 4 3 4 4 4 4 4 0 0 0 0 0 0 0 0 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 3 3 3 3 3\n",
+      " 3 3 3 4 4 4 4 4 4 4 4 0 1 0 0 0 0 0 0 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 3 3\n",
+      " 3 3 3 3 3 3 1 4 3 4 4 4 4 4 0 0 0 0 0 0 0 0 2 3 2 2 2 2 2 2]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(abc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "predictions = (lb.inverse_transform((abc)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>predictedvalues</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  predictedvalues\n",
+       "0       male_calm\n",
+       "1       male_calm\n",
+       "2       male_calm\n",
+       "3       male_calm\n",
+       "4       male_calm\n",
+       "5       male_calm\n",
+       "6       male_calm\n",
+       "7       male_calm\n",
+       "8      male_happy\n",
+       "9      male_happy"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "preddf = pd.DataFrame({'predictedvalues': predictions})\n",
+    "preddf[:10]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "actual=test_valid_lb.argmax(axis=1)\n",
+    "abc123 = actual.astype(int).flatten()\n",
+    "actualvalues = (lb.inverse_transform((abc123)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>actualvalues</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  actualvalues\n",
+       "0    male_calm\n",
+       "1    male_calm\n",
+       "2    male_calm\n",
+       "3    male_calm\n",
+       "4    male_calm\n",
+       "5    male_calm\n",
+       "6    male_calm\n",
+       "7    male_calm\n",
+       "8   male_happy\n",
+       "9   male_happy"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "actualdf = pd.DataFrame({'actualvalues': actualvalues})\n",
+    "actualdf[:10]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "finaldf = actualdf.join(preddf)\n",
+    "#abc1234 = finaldf.astype(float).flatten()\n",
+    "#finalvalues = (lb.inverse_transform((abc1234)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Actual vs Predicted Values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>actualvalues</th>\n",
+       "      <th>predictedvalues</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>male_calm</td>\n",
+       "      <td>male_sad</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>male_calm</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>male_calm</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>male_calm</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>male_calm</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>male_calm</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>male_calm</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>male_calm</td>\n",
+       "      <td>male_calm</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>male_happy</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>male_happy</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>male_happy</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>male_happy</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>male_happy</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>male_happy</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>54</th>\n",
+       "      <td>male_happy</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>55</th>\n",
+       "      <td>male_happy</td>\n",
+       "      <td>male_happy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56</th>\n",
+       "      <td>male_sad</td>\n",
+       "      <td>male_sad</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57</th>\n",
+       "      <td>male_sad</td>\n",
+       "      <td>male_sad</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58</th>\n",
+       "      <td>male_sad</td>\n",
+       "      <td>male_sad</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>59</th>\n",
+       "      <td>male_sad</td>\n",
+       "      <td>male_sad</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   actualvalues predictedvalues\n",
+       "40    male_calm        male_sad\n",
+       "41    male_calm       male_calm\n",
+       "42    male_calm       male_calm\n",
+       "43    male_calm       male_calm\n",
+       "44    male_calm       male_calm\n",
+       "45    male_calm       male_calm\n",
+       "46    male_calm       male_calm\n",
+       "47    male_calm       male_calm\n",
+       "48   male_happy      male_happy\n",
+       "49   male_happy      male_happy\n",
+       "50   male_happy      male_happy\n",
+       "51   male_happy      male_happy\n",
+       "52   male_happy      male_happy\n",
+       "53   male_happy      male_happy\n",
+       "54   male_happy      male_happy\n",
+       "55   male_happy      male_happy\n",
+       "56     male_sad        male_sad\n",
+       "57     male_sad        male_sad\n",
+       "58     male_sad        male_sad\n",
+       "59     male_sad        male_sad"
+      ]
+     },
+     "execution_count": 83,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "finaldf[40:60]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>predictedvalues</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>actualvalues</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>male_angry</th>\n",
+       "      <td>80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>male_calm</th>\n",
+       "      <td>80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>male_fearful</th>\n",
+       "      <td>80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>male_happy</th>\n",
+       "      <td>80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>male_sad</th>\n",
+       "      <td>80</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              predictedvalues\n",
+       "actualvalues                 \n",
+       "male_angry                 80\n",
+       "male_calm                  80\n",
+       "male_fearful               80\n",
+       "male_happy                 80\n",
+       "male_sad                   80"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "finaldf.groupby('actualvalues').count()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>actualvalues</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>predictedvalues</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>male_angry</th>\n",
+       "      <td>79</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>male_calm</th>\n",
+       "      <td>78</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>male_fearful</th>\n",
+       "      <td>71</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>male_happy</th>\n",
+       "      <td>87</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>male_sad</th>\n",
+       "      <td>85</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 actualvalues\n",
+       "predictedvalues              \n",
+       "male_angry                 79\n",
+       "male_calm                  78\n",
+       "male_fearful               71\n",
+       "male_happy                 87\n",
+       "male_sad                   85"
+      ]
+     },
+     "execution_count": 85,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "finaldf.groupby('predictedvalues').count()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "finaldf.to_csv('E:\\\\8th sem\\\\Final_Year_Project_Files\\\\New Folder\\\\Predictions.csv', index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def print_confusion_matrix(confusion_matrix, class_names, figsize = (10,7), fontsize=14):\n",
+    "    \"\"\"Prints a confusion matrix, as returned by sklearn.metrics.confusion_matrix, as a heatmap.\n",
+    "    \n",
+    "    Arguments\n",
+    "    ---------\n",
+    "    confusion_matrix: numpy.ndarray\n",
+    "        The numpy.ndarray object returned from a call to sklearn.metrics.confusion_matrix. \n",
+    "        Similarly constructed ndarrays can also be used.\n",
+    "    class_names: list\n",
+    "        An ordered list of class names, in the order they index the given confusion matrix.\n",
+    "    figsize: tuple\n",
+    "        A 2-long tuple, the first value determining the horizontal size of the ouputted figure,\n",
+    "        the second determining the vertical size. Defaults to (10,7).\n",
+    "    fontsize: int\n",
+    "        Font size for axes labels. Defaults to 14.\n",
+    "        \n",
+    "    Returns\n",
+    "    -------\n",
+    "    matplotlib.figure.Figure\n",
+    "        The resulting confusion matrix figure\n",
+    "    \"\"\"\n",
+    "    df_cm = pd.DataFrame(\n",
+    "        confusion_matrix, index=class_names, columns=class_names, \n",
+    "    )\n",
+    "    fig = plt.figure(figsize=figsize)\n",
+    "    try:\n",
+    "        heatmap = sns.heatmap(df_cm, annot=True, fmt=\"d\")\n",
+    "    except ValueError:\n",
+    "        raise ValueError(\"Confusion matrix values must be integers.\")\n",
+    "        \n",
+    "    heatmap.yaxis.set_ticklabels(heatmap.yaxis.get_ticklabels(), rotation=0, ha='right', fontsize=fontsize)\n",
+    "    heatmap.xaxis.set_ticklabels(heatmap.xaxis.get_ticklabels(), rotation=45, ha='right', fontsize=fontsize)\n",
+    "    plt.ylabel('True label')\n",
+    "    plt.xlabel('Predicted label')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "94.25"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import accuracy_score\n",
+    "y_true = finaldf.actualvalues\n",
+    "y_pred = finaldf.predictedvalues\n",
+    "accuracy_score(y_true, y_pred)*100"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "94.2642441006739"
+      ]
+     },
+     "execution_count": 89,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import f1_score\n",
+    "f1_score(y_true, y_pred, average='macro') *100"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[79,  1,  0,  0,  0],\n",
+       "       [ 0, 73,  0,  2,  5],\n",
+       "       [ 0,  0, 71,  3,  6],\n",
+       "       [ 0,  0,  0, 80,  0],\n",
+       "       [ 0,  4,  0,  2, 74]], dtype=int64)"
+      ]
+     },
+     "execution_count": 90,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import confusion_matrix\n",
+    "c = confusion_matrix(y_true, y_pred)\n",
+    "c"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x504 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Visualize Confusion Matrix \n",
+    "\n",
+    "class_names = ['male_angry', 'male_calm', 'male_fearful', 'male_happy', 'male_sad']\n",
+    "#class_names1 = ['female_angry', 'female_calm', 'female_fearful', 'female_happy', 'female_sad']\n",
+    "#class_names = ['male_negative', 'male_neutral', 'male_positive']\n",
+    "#class_names = ['male_negative', 'male_positive']\n",
+    "#class_names = ['female_angry', 'female_calm', 'female_fearful', 'female_happy', 'female_sad', 'male_angry', 'male_calm', 'male_fearful', 'male_happy', 'male_sad']\n",
+    "\n",
+    "\n",
+    "print_confusion_matrix(c, class_names)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
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+}