https://github.com/mignonne-patterson/musicshadow
A Matlab-based audio processing tool that uses shadowsocks for secure and efficient music streaming.
https://github.com/mignonne-patterson/musicshadow
Last synced: 2 months ago
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A Matlab-based audio processing tool that uses shadowsocks for secure and efficient music streaming.
- Host: GitHub
- URL: https://github.com/mignonne-patterson/musicshadow
- Owner: Mignonne-Patterson
- License: other
- Created: 2025-03-21T06:01:41.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-03-21T06:01:51.000Z (3 months ago)
- Last Synced: 2025-03-21T07:25:07.689Z (3 months ago)
- Language: MATLAB
- Size: 30.3 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# MusicShadow: A Secure and Enhanced Audio Processing Tool
## Overview
MusicShadow is a Matlab-based audio processing tool that leverages shadowsocks for secure and efficient music streaming. This project aims to enhance the listening experience by applying advanced signal processing techniques while ensuring data privacy through a robust proxy system. Whether you are a music enthusiast, an audiophile, or a researcher in audio engineering, MusicShadow offers a comprehensive solution for managing your music library and enjoying high-quality audio streams with peace of mind.
## Key Features
- **Secure Data Streaming:** Utilizes shadowsocks to encrypt data transmission, ensuring privacy and security.
- **Advanced Audio Processing:** Applies advanced signal processing techniques to enhance sound quality.
- **User-Friendly Interface:** Provides a seamless and intuitive user experience for managing music libraries.
- **Cross-Platform Compatibility:** Runs on various operating systems, including Windows, macOS, and Linux.
## Installation
To install MusicShadow, please follow these steps:
1. Download the latest version of the project from the [MusicShadow GitHub repository](https://github.com/Mignonne-Patterson/MusicShadow).
2. Install [MATLAB](https://www.mathworks.com/products/matlab.html) on your computer.
3. Ensure that shadowsocks is installed and configured on your system for secure internet access.
4. Open the downloaded project folder in MATLAB.
5. Run the main script to launch MusicShadow.
## Usage
MusicShadow offers a variety of functionalities to cater to different user needs:
- **Stream Management:** Easily manage music streams from various sources, including local files and online platforms.
- **Signal Processing Tools:** Utilize advanced signal processing algorithms for noise reduction, equalization, and other audio enhancements.
- **Privacy Features:** Secure your data transmissions using shadowsocks to protect against unauthorized access and eavesdropping.
## Development
MusicShadow is actively developed by a team of researchers and engineers dedicated to improving the project's performance and features. Contributions are welcome from anyone interested in enhancing the tool or expanding its capabilities.
To contribute to MusicShadow, please follow these guidelines:
- Fork the [MusicShadow GitHub repository](https://github.com/Mignonne-Patterson/MusicShadow).
- Create a new branch for your feature or bug fix.
- Implement your changes and test thoroughly.
- Submit a pull request with detailed information about your contribution.
## Support
For any issues, questions, or feedback regarding MusicShadow, please contact the development team via [GitHub Issues](https://github.com/Mignonne-Patterson/MusicShadow/issues) or reach out to us directly at [email protected].
We appreciate your interest in MusicShadow and look forward to enhancing your music listening experience with this innovative tool!
## License
MusicShadow is licensed under the MIT license. Please refer to the [LICENSE](https://github.com/Mignonne-Patterson/MusicShadow/blob/main/LICENSE) file for more details.