Setup

Prerequisites

• Python 3.x
• [List other required software, e.g., CUDA for GPU support]

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/yourproject.git
   cd yourproject

2. Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

Data Preparation

1. Place your raw audio files in the data/raw/ directory.
2. Run the preprocessing script to process the raw audio files:

   python src/data_preprocessing.py

Training the Model

1. Run the training script:

   python src/train.py

Running Inference

1. Run the inference script to make predictions on new audio files:

   python src/inference.py

Project Details

Data

• raw/: Contains raw audio files for inference.
• processed/: Contains processed audio files.

Models

• models/: Contains trained model files and checkpoints.

Source Code

• src/data_preprocessing.py: Script for data preprocessing.
• src/inference.py: Script for running inference.
• src/train.py: Script for training the model.

Notebooks

• notebooks/: Contains Jupyter notebooks for data analysis and exploration.

Tests

• tests/: Contains unit tests for the project's codebase.

Contributing

Contributions are welcome! Please follow these steps to contribute:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Commit your changes (git commit -m 'Add some feature').
4. Push to the branch (git push origin feature-branch).
5. Open a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

• [List any resources, libraries, or individuals you want to acknowledge]

Contact

• [Your Name] - [[email protected]]
• Project Link: https://github.com/yourusername/yourproject