Applio

Local Gradio app for RVC voice conversion, voice model training, realtime conversion and TTS.

Open SourceSelf HostedOffline CapableGPU Required (4GB+ VRAM)
0.0 (0)

About

Applio wraps Retrieval-based Voice Conversion in a local Gradio app maintained by the AI Hispano community. You load or download an RVC voice model, feed in a vocal recording, and get the same performance sung or spoken in the target voice. The interface also trains new voice models from your own clean dataset with TensorBoard monitoring, and adds realtime conversion for a live microphone, text-to-speech routed through a voice model, a blender that merges two voice models, an audio analyzer, a model downloader and plugins. Install with the run-install script on Windows, Linux or macOS or a precompiled Windows zip, with Docker and Colab as alternatives; conversion works on CPU, training is far quicker on an NVIDIA GPU or a cloud notebook, and AMD on Windows has a ZLUDA guide. Code and bundled weights are MIT, so commercial use is allowed, though the unmodified official build also carries a terms-of-use file requiring lawful, consented use. Maintainers call it mature and now ship mostly security and dependency updates, with occasional features. Suited to cover makers and developers who want RVC without assembling the toolchain.

Should you use Applio?

Pick it when

Pick Applio when you want to train and run RVC voice models from your own recordings on a 4 GB GPU in one friendly interface that bundles training, inference, a realtime tab, TensorBoard monitoring, model fusion, and plugins.

Look elsewhere when

Skip it if you lack minutes of clean target audio, since every voice needs a training run; OpenVoice or GPT-SoVITS clone from seconds. For live use with Beatrice or DDSP-SVC models, or with no GPU at all, W-Okada Voice Changer covers more ground.

Alternatives to Applio

  • RVC (Retrieval-based Voice Conversion)

    The upstream reference project with RMVPE pitch extraction and a documented 170 ms real-time path, but a plainer UI with no plugin system.

  • W-Okada Voice Changer

    Download-and-run live client that also loads Beatrice, MMVC, and DDSP-SVC models and can work without a GPU, but it cannot train a voice.

  • GPT-SoVITS

    Fine-tunes from about one minute of audio and bundles text-to-speech with conversion, but needs 6 GB of VRAM versus 4 GB.

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Details

Price
Free
Platform
Local/Desktop
Difficulty
Easy (2/5)
License
MIT
Minimum VRAM
4 GB
Added
Apr 3, 2026

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