Updated README.md file

Author: GenaNiv

README.md

@@ -13,12 +13,47 @@ to perform accurate and robust speaker identification.
 1. **Clone the Repository**
    ```bash
    git clone https://github.com/your_username/your_repository_name.git
-   cd your_repository_name```
+   cd your_repository_name
 
 2. **Install Dependencies**
    ```bash
-   pip install -r requirements.txt```
+   pip install -r requirements.txt
 
 3. **Verify the Installation**
    ```bash
-   python cli.py --help```
+   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:
+
+```bash
+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:**
+```bash
+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