/Applio

Ultimate voice cloning tool, meticulously optimized for unrivaled power, modularity, and user-friendly experience.

Primary LanguagePythonOtherNOASSERTION

Applio

Welcome to Applio, the ultimate voice cloning tool meticulously optimized for unrivaled power, modularity, and a user-friendly experience.

🍏 Applio Plugins Compiled Versions GitHub Release GitHub Repo stars GitHub forks Support Discord Issues Open In Collab

Content Table

Installation

Download the latest version from GitHub Releases or use Precompiled Versions.

Windows

./run-install.bat

Linux

chmod +x run-install.sh
./run-install.sh

Using Makefile (for platforms such as Paperspace)

make run-install

Usage

Visit Applio Documentation for a detailed UI usage explanation.

Windows

./run-applio.bat

Linux

chmod +x run-applio.sh
./run-applio.sh

Using Makefile (for platforms such as Paperspace)

make run-applio

Repository Enhancements

This repository has undergone significant enhancements to improve its functionality and maintainability:

  • Modular Codebase: Restructured codebase following a modular approach for better organization, readability, and maintenance.
  • Hop Length Implementation: Implemented hop length, courtesy of @Mangio621, boosting efficiency and performance, especially on Crepe (formerly Mangio-Crepe).
  • Translations in 30+ Languages: Added support for translations in over 30 languages, enhancing accessibility for a global audience.
  • Cross-Platform Compatibility: Ensured seamless operation across various platforms for a consistent user experience.
  • Optimized Requirements: Fine-tuned project requirements for enhanced performance and resource efficiency.
  • Streamlined Installation: Simplified installation process for a user-friendly setup experience.
  • Hybrid F0 Estimation: Introduced a personalized 'hybrid' F0 estimation method utilizing nanmedian, combining F0 calculations from various methods to achieve optimal results.
  • Easy-to-Use UI: Implemented a user-friendly interface for intuitive interaction.
  • Optimized Code & Dependencies: Enhanced code and streamlined dependencies for improved efficiency.
  • Plugin System: Introduced a plugin system for extending functionality and customization.

These enhancements contribute to a more robust and scalable codebase, making the repository more accessible for contributors and users alike.

Contributions

  • Backend Contributions: If you want to contribute to the backend, make your pull requests here.
  • Frontend Contributions: For interface or script-related contributions, feel free to contribute to this repository.

We appreciate all contributions ❤️

Planned Features

  • Implement: Support training for Apple Devices
  • Implement: rmvpe_gpu
  • Implement: Overtraining detector
  • Implement: Training stop
  • Fix: Model fusion

Credits

Contributors