Speaker Recognition Engine

The Speaker Recognition Engine is a command-line tool for managing speaker audio data. It supports the following functionalities:

• Enrolling new speakers
• Recognizing speakers from audio samples
• Listing all enrolled speakers
• Deleting speaker records

The engine leverages machine learning techniques, specifically Gaussian Mixture Models (GMM), to perform accurate and robust speaker identification.

Installation

1. Clone the Repository

   git clone [email protected]:GenaNiv/voice-recognition-engine.git
   cd voice-recognition-engine
   

2. Install Dependencies

   pip install -r requirements.txt
   

3. Verify the Installation

   python cli.py --help
   

Usage

The Speaker Recognition Engine supports several commands for managing speaker audio data. Below are the available commands:

1. Enroll a Speaker: Enroll a new speaker using an audio file.
2. Recognize a Speaker: Identify a speaker from a given audio file.
3. List Enrolled Speakers: Display a list of all enrolled speakers.
4. Delete a Speaker: Remove a speaker's data from the system.

Each command can be executed from the command line with the appropriate arguments. The general syntax for using the tool is:

python cli.py <command> [arguments]

Enroll a Speaker

To enroll a new speaker, use the enroll command followed by the speaker's name and the path to the audio file. Optionally, you can specify parameters like sample rate, number of filters, and number of MFCC coefficients.

Syntax:

python cli.py enroll <speaker_name> <audio_file_path> [optional parameters]

Optional Parameters:

• --sample_rate: Sampling rate of the audio file (default: 16000)
• --num_filters: Number of Mel filters (default: 26)
• --num_ceps: Number of MFCC coefficients (default: 13)
• --n_fft: FFT size for audio processing (default: 512)
• --frame_size: Frame size in seconds (default: 0.025)
• --frame_step: Frame step (overlap) in seconds (default: 0.01)
• --n_mixtures: Number of Gaussian mixtures in GMM (default: 8)

Example:

python cli.py enroll gena /home/gena/audio_files/gena.wav --sample_rate 16000 --num_filters 40 --num_ceps 13 --n_fft 512 --frame_size 0.025 --frame_step 0.01 --n_mixtures 8