Retrieval-based-Voice-Conversion-WebUI
Easily train a good VC model with voice data <= 10 mins!
A simple, high-quality RVC voice conversion tool focused on ease of use and performance.
Applio is an open-source audio project by IAHispano (IAHispano/Applio on GitHub). It has 3,806 GitHub stars and 602 forks, is released under the MIT license, and was last updated on GitHub on 5 October 2026.
Decide the first concrete outcome you want from it, so you can pick the right example, template or mode instead of exploring everything at once.
Clone the repository (or install the published package) and skim its README quick start for the requirements for your platform.
Run the documented install step and set any required configuration — such as provider keys, data sources or local services — before the first run.
Execute the smallest documented example end to end, confirm the output is what you expected, then adapt it to your real data or workflow.
Convert voice recordings to a target voice with a pipeline focused on quality and performance.
Train your own voice models inside the tool, with optional TensorBoard monitoring.
One-click install scripts — run-install.bat on Windows, run-install.sh on Linux/macOS.
Extend Applio through the separate Applio-Plugins collection and custom configurations.
Compiled versions are published on the project's Hugging Face space for a quicker start.
The maintainers describe the project as stable and mature, with an active community on Discord.
Get the source so you can inspect, configure and run it locally.
git clone https://github.com/IAHispano/Applio.git
cd ApplioClone the repo, then run the installer for your platform.
git clone https://github.com/IAHispano/Applio.git
cd Applio
./run-install.sh # Windows: run-install.batStart Applio and open the web UI to train a model or convert a recording.
./run-applio.sh # Windows: run-applio.batIt is maintained by IAHispano on GitHub (IAHispano/Applio), where the source, issues and releases live.
Yes — it is free and open source under the MIT licence, which permits use, modification and redistribution, including commercially, with attribution.
No — Applio runs locally on your own GPU/CPU and needs no paid API key; use it only with voices you have the right to use.
Compared with the original RVC WebUI, Applio's distinguishing focus is: a simple, high-quality RVC voice conversion tool focused on ease of use and performance. Pick it when that focus matches your need; the alternative may suit you better if its broader or different scope is the priority.
Clone https://github.com/IAHispano/Applio (or install its published package), follow the README quick start to install and configure it, then run the smallest documented example — the Run section on this page mirrors those steps.
Easily train a good VC model with voice data <= 10 mins!
Open research toolkit for text-to-speech, voice conversion, singing voice and text-to-audio generation.
A pure C++ ggml inference engine for audio models — TTS, STT, VAD, voice conversion and music.
GPA — one tiny model that does ASR, TTS and voice conversion (General Purpose Audio).
GAN vocoder that turns mel-spectrograms into high-fidelity speech audio, fast enough for real-time use.
Fish Speech — Fish Audio's expressive open text-to-speech and voice cloning: SOTA-quality TTS you can self-host, under the Fish Audio Community License (check terms)
The most-starred other Audio projects in the LibreAI catalogue — the realistic shortlist if Applio is not the right fit.
利用 AI 大模型和自动化工作流,根据主题或关键词一键生成高清短视频。Generate HD short videos from a topic or keyword with an automated AI workflow.
Robust Speech Recognition via Large-Scale Weak Supervision
1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
Clone a voice from 5 seconds of audio and generate arbitrary speech in real time
Port of OpenAI's Whisper model in C/C++
Free and open — grab the source, star the repo, and start creating.