Retrieval-based-Voice-Conversion-WebUI

An easy-to-use Voice Conversion framework based on VITS.

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------ [**Changelog**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/docs/Changelog_EN.md) | [**FAQ (Frequently Asked Questions)**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/FAQ-(Frequently-Asked-Questions)) [**English**](./README.en.md) | [**中文简体**](../README.md) | [**日本語**](./README.ja.md) | [**한국어**](./README.ko.md) ([**韓國語**](./README.ko.han.md)) Check our [Demo Video](https://www.bilibili.com/video/BV1pm4y1z7Gm/) here! Realtime Voice Conversion Software using RVC : [w-okada/voice-changer](https://github.com/w-okada/voice-changer) > A online demo using RVC that convert Vocal to Acoustic Guitar audio:https://huggingface.co/spaces/lj1995/vocal2guitar > Vocal2Guitar demo video:https://www.bilibili.com/video/BV19W4y1D7tT/ > The dataset for the pre-training model uses nearly 50 hours of high quality VCTK open source dataset. > High quality licensed song datasets will be added to training-set one after another for your use, without worrying about copyright infringement. ## Summary This repository has the following features: + Reduce tone leakage by replacing the source feature to training-set feature using top1 retrieval; + Easy and fast training, even on relatively poor graphics cards; + Training with a small amount of data also obtains relatively good results (>=10min low noise speech recommended); + Supporting model fusion to change timbres (using ckpt processing tab->ckpt merge); + Easy-to-use Webui interface; + Use the UVR5 model to quickly separate vocals and instruments. + Use the most powerful High-pitch Voice Extraction Algorithm [InterSpeech2023-RMVPE](#Credits) to prevent the muted sound problem. Provides the best results (significantly) and is faster, with even lower resource consumption than Crepe_full. ## Preparing the environment The following commands need to be executed in the environment of Python version 3.8 or higher. (Windows/Linux) First install the main dependencies through pip: ```bash # Install PyTorch-related core dependencies, skip if installed # Reference: https://pytorch.org/get-started/locally/ pip install torch torchvision torchaudio #For Windows + Nvidia Ampere Architecture(RTX30xx), you need to specify the cuda version corresponding to pytorch according to the experience of https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/issues/21 #pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117 ``` Then can use poetry to install the other dependencies: ```bash # Install the Poetry dependency management tool, skip if installed # Reference: https://python-poetry.org/docs/#installation curl -sSL https://install.python-poetry.org | python3 - # Install the project dependencies poetry install ``` You can also use pip to install them: ```bash pip install -r requirements.txt ``` ------ Mac users can install dependencies via `run.sh`: ```bash sh ./run.sh ``` ## Preparation of other Pre-models RVC requires other pre-models to infer and train. You need to download them from our [Huggingface space](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/). Here's a list of Pre-models and other files that RVC needs: ```bash hubert_base.pt ./pretrained ./uvr5_weights If you want to test the v2 version model (the v2 version model has changed the input from the 256 dimensional feature of 9-layer Hubert+final_proj to the 768 dimensional feature of 12-layer Hubert, and has added 3 period discriminators), you will need to download additional features ./pretrained_v2 #If you are using Windows, you may also need this dictionary, skip if FFmpeg is installed ffmpeg.exe ``` Then use this command to start Webui: ```bash python infer-web.py ``` If you are using Windows or macOS, you can download and extract `RVC-beta.7z` to use RVC directly by using `go-web.bat` on windows or `sh ./run.sh` on macOS to start Webui. There's also a tutorial on RVC in Chinese and you can check it out if needed. ## Credits + [ContentVec](https://github.com/auspicious3000/contentvec/) + [VITS](https://github.com/jaywalnut310/vits) + [HIFIGAN](https://github.com/jik876/hifi-gan) + [Gradio](https://github.com/gradio-app/gradio) + [FFmpeg](https://github.com/FFmpeg/FFmpeg) + [Ultimate Vocal Remover](https://github.com/Anjok07/ultimatevocalremovergui) + [audio-slicer](https://github.com/openvpi/audio-slicer) + [Vocal pitch extraction:RMVPE](https://github.com/Dream-High/RMVPE) + The pretrained model is trained and tested by [yxlllc](https://github.com/yxlllc/RMVPE) and [RVC-Boss](https://github.com/RVC-Boss). ## Thanks to all contributors for their efforts