# speaker_recognition_GMM_UBM

A speaker recognition system which uses GMM-UBM for use in an Android application which helps in monitoring patients suffering from Schizophrenia.

### Installing dependencies

To install all the dependencies for this project, run the following command,

```

pip3 install -r requirements.txt

```

### Extracing MFCC from audio

- - -

To extract MFCC coefficients from audio samples, put all the audio files in a seperate folder and run the following command,

```

python3 src/speaker_recognition/extract_mfcc_coefficients.py

--audio_folder <path to the folder which contains audio>

--csv_file_name <name of the csv file that will be created>

--opt combined

```

### Creating Universal Background Model

- - -

To run UBM training run the following code,

```

python3 src/speaker_recognition/speaker_recognition.py 

--csv_file <path to MFCC coefficients file> 

--operation ubm

```

### Map adaptation using the created GMM-UBM model

- - -

To run MAP adaptation,

```

python3 src/speaker_recognition/speaker_recognition.py 

--csv_file <path to MFCC coefficients file> 

--operation map 

--ubm_file <path to the ubm file created after GMM-UBM model creation>

```

For testing the map adapted model,

```

python3 src/speaker_recognition/testing_model.py

--map_file_name <path to map adapted .npy file>

--ubm_file_name <path to ubm .npy file>

--test_csv_file <path to the csv file of test speaker>

--N 1500

```