This project implements a song recognition algorithm inspired by Shazam, utilizing deep learning and natural language processing techniques. The system processes audio signals, extracts features, and matches them against a database of known songs.

shazam-python
├── src
│   ├── audio_processing
│   ├── fingerprinting
│   ├── models
│   ├── database
│   ├── visualization
│   ├── utils
│   └── app.py
├── tests
├── data
├── notebooks
├── config.yaml
├── requirements.txt
├── setup.py
└── README.md

1. Clone the repository:

   git clone https://github.com/yourusername/shazam-python.git
   cd shazam-python
   

2. Install the required packages:

   pip install -r requirements.txt
   

To run the application, execute the following command:

python src/app.py

• Audio Processing: Implements filtering, FFT, and spectrogram generation.
• Fingerprinting: Extracts peaks and generates unique audio fingerprints.
• Matching: Matches audio fingerprints against a database of known songs.
• Visualization: Visualizes spectrograms and audio features.

To run the tests, use:

pytest tests/

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

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