{"id":25862703,"url":"https://github.com/digisoch/noise_remover-webapp","last_synced_at":"2026-06-09T19:31:32.074Z","repository":{"id":269271968,"uuid":"905136766","full_name":"DigiSoch/noise_remover-webapp","owner":"DigiSoch","description":"A web-based application that reduces background noise from audio files using spectral noise reduction techniques. 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The application provides a user-friendly interface for uploading audio files, adjusting noise reduction parameters, and downloading the processed results.\n\n## Features\n\n- Upload audio files in multiple formats (WAV, MP3, OGG, FLAC, M4A)\n- Adjustable noise reduction strength (0.1 - 6.0)\n- Real-time processing progress indication\n- Audio preview player with playback controls\n- Multiple output format options (WAV, MP3, OGG, FLAC)\n- Download processed audio files\n\n## Prerequisites\n\n- Python 3.7+\n- FFmpeg installed on the system\n- Web browser with HTML5 audio support\n\n## Installation\n\n1. Clone the repository:\n   \n```\ngit clone [https://github.com/arvind-git-code/noise_remover-webapp.git](https://github.com/arvind-git-code/noise_remover-webapp.git)\ncd audio-noise-reducer\n```\n\n2. Create and activate a virtual environment (recommended):\n```bash\npython -m venv venv\nsource venv/bin/activate  # On Windows: venv\\Scripts\\activate\n```\n\n3. Install the required Python packages:\n```bash\npip install -r requirements.txt\n```\n\n4. Install FFmpeg:\n- **Ubuntu/Debian**:\n  ```bash\n  sudo apt-get update\n  sudo apt-get install ffmpeg\n  ```\n- **Windows**: Download from [FFmpeg website](https://ffmpeg.org/download.html)\n- **macOS**:\n  ```bash\n  brew install ffmpeg\n  ```\n\n## Configuration\n\n1. Create an `uploads` directory in the project root:\n```bash\nmkdir uploads\n```\n\n2. (Optional) Adjust the following settings in `app.py`:\n- `MAX_CONTENT_LENGTH`: Maximum upload file size (default: 500MB)\n- `SECRET_KEY`: Flask application secret key\n- Server host and port in `app.run()`\n\n## Usage\n\n1. Start the Flask server:\n```bash\npython app.py\n```\n\n2. Open a web browser and navigate to:\n```\nhttp://localhost:5000\n```\n\n3. Using the application:\n   - Click \"Choose File\" to select an audio file\n   - Adjust the noise reduction strength slider (higher values = stronger reduction)\n   - Select desired output format\n   - Click \"Process Audio\" to start noise reduction\n   - Wait for processing to complete\n   - Preview the processed audio using the built-in player\n   - Click \"Download\" to save the processed file\n\n## Technical Details\n\n### Noise Reduction Algorithm\n\nThe application uses the Short-Time Fourier Transform (STFT) for spectral noise reduction:\n1. Converts audio to frequency domain using STFT\n2. Estimates noise profile from the first few frames\n3. Creates and applies a spectral subtraction mask\n4. Smooths the mask using median filtering\n5. Converts back to time domain using inverse STFT\n\n### File Processing\n\n- Input files are automatically converted to WAV format for processing\n- Supports mono and stereo audio (stereo is converted to mono)\n- Audio is normalized before processing\n- Processed files are converted to the selected output format using FFmpeg\n\n## API Endpoints\n\n- `GET /`: Main application interface\n- `POST /upload`: Upload and process audio file\n- `GET /status/\u003ctask_id\u003e`: Get processing status\n- `GET /download/\u003ctask_id\u003e`: Download processed file\n\n## Error Handling\n\n- Invalid file types are rejected\n- Processing errors are displayed in the UI\n- Failed tasks are automatically cleaned up\n- Temporary files are removed after processing\n\n## Security Features\n\n- Secure filename handling\n- File type validation\n- Maximum file size limit\n- CORS support for API access\n\n## Browser Compatibility\n\nTested and supported on:\n- Chrome 80+\n- Firefox 75+\n- Safari 13+\n- Edge 80+\n\n## Known Limitations\n\n- Large files may take significant time to process\n- Processing is CPU-intensive\n- Memory usage scales with file size\n- Browser audio preview may not support all formats\n\n## Contributing\n\n1. Fork the repository\n2. Create a feature branch\n3. Commit your changes\n4. Push to the branch\n5. Create a Pull Request\n\n\n## Connect with me\n\n- **Name:** Arvind Kumar\n- **LinkedIn:** [LinkedIn Profile URL](https://www.linkedin.com/in/arvind-kumar-a8b591221/)\n- **Email:** [Email](mailto:arvindkumarlbsmca@gmail.com)\n\n\n\n## License\n\nFeel free to use anywhere\n\n\n\n## Acknowledgments\n\n- FFmpeg for audio format conversion\n- SciPy for signal processing\n- Flask for web framework\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdigisoch%2Fnoise_remover-webapp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdigisoch%2Fnoise_remover-webapp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdigisoch%2Fnoise_remover-webapp/lists"}