
Applio
A simple, high-quality voice conversion tool focused on ease of use and performance.
Stars: 2586

Applio is a VITS-based Voice Conversion tool focused on simplicity, quality, and performance. It features a user-friendly interface, cross-platform compatibility, and a range of customization options. Applio is suitable for various tasks such as voice cloning, voice conversion, and audio editing. Its key features include a modular codebase, hop length implementation, translations in over 30 languages, optimized requirements, streamlined installation, hybrid F0 estimation, easy-to-use UI, optimized code and dependencies, plugin system, overtraining detector, model search, enhancements in pretrained models, voice blender, accessibility improvements, new F0 extraction methods, output format selection, hashing system, model download system, TTS enhancements, split audio, Discord presence, Flask integration, and support tab.
README:
A simple, high-quality voice conversion tool, focused on ease of use and performance.
🌐 Website • 📚 Documentation • ☎️ Discord
🛒 Plugins • 📦 Compiled • 🎮 Playground • 🔎 Google Colab (UI) • 🔎 Google Colab (No UI)
[!NOTE]
Applio will no longer receive frequent updates. Going forward, development will focus mainly on security patches, dependency updates, and occasional feature improvements. This is because the project is already stable and mature with limited room for further improvements. Pull requests are still welcome and will be reviewed.
Applio is a powerful voice conversion tool focused on simplicity, quality, and performance. Whether you're an artist, developer, or researcher, Applio offers a straightforward platform for high-quality voice transformations. Its flexible design allows for customization through plugins and configurations, catering to a wide range of projects.
Using Applio responsibly is essential.
- Users must respect copyrights, intellectual property, and privacy rights.
- Applio is intended for lawful and ethical purposes, including personal, academic, and investigative projects.
- Commercial usage is permitted, provided users adhere to legal and ethical guidelines, secure appropriate rights and permissions, and comply with the MIT license.
The source code and model weights in this repository are licensed under the permissive MIT license, allowing modification, redistribution, and commercial use.
However, if you choose to use this official version of Applio (as provided in this repository, without significant modification), you must also comply with our Terms of Use. These terms apply to our integrations, configurations, and default project behavior, and are intended to ensure responsible and ethical use without limiting their use in any way.
For commercial use, we recommend contacting us at [email protected] to ensure your usage aligns with ethical standards. All audio generated with Applio must comply with applicable copyright laws. If you find Applio helpful, consider supporting its development through a donation.
By using the official version of Applio, you accept full responsibility for complying with both the MIT license and our Terms of Use. Applio and its contributors are not liable for misuse. For full legal details, see the Terms of Use.
Run the installation script based on your operating system:
-
Windows: Double-click
run-install.bat
. -
Linux/macOS: Execute
run-install.sh
.
Start Applio using:
-
Windows: Double-click
run-applio.bat
. -
Linux/macOS: Run
run-applio.sh
.
This launches the Gradio interface in your default browser.
To monitor training or visualize data:
-
Windows: Run
run-tensorboard.bat
. -
Linux/macOS: Run
run-tensorboard.sh
.
For more detailed instructions, visit the documentation.
Applio is made possible thanks to these projects and their references:
- gradio-screen-recorder by gstaff
- rvc-cli by blaisewf
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