Retrieval-based-Voice-Conversion-WebUI
An easy-to-use Voice Conversion framework based on VITS.
[](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI)
[](https://colab.research.google.com/github/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/Retrieval_based_Voice_Conversion_WebUI.ipynb)
[](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/LICENSE)
[](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/)
[](https://discord.gg/HcsmBBGyVk)
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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**](../en/README.en.md) | [**ä¸æ–‡ç®€ä½“**](../../README.md) | [**日本語**](../jp/README.ja.md) | [**í•œêµì–´**](../kr/README.ko.md) ([**韓國語**](../kr/README.ko.han.md)) | [**Türkçe**](../tr/README.tr.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)
> 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.
> Please look forward to the pretrained base model of RVCv3, which has larger parameters, more training data, better results, unchanged inference speed, and requires less training data for training.
## 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.
+ AMD/Intel graphics cards acceleration supported.
+ Intel ARC graphics cards acceleration with IPEX supported.
## 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
for Nvidia graphics cards
pip install -r requirements.txt
for AMD/Intel graphics cards：
pip install -r requirements-dml.txt
for Intel ARC graphics cards on Linux / WSL using Python 3.10:
pip install -r requirements-ipex.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
./assets/hubert/hubert_base.pt
./assets/pretrained
./assets/uvr5_weights
Additional downloads are required if you want to test the v2 version of the model.
./assets/pretrained_v2
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
./assets/pretrained_v2
#If you are using Windows, you may also need these two files, skip if FFmpeg and FFprobe are installed
ffmpeg.exe
https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe
ffprobe.exe
https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe
If you want to use the latest SOTA RMVPE vocal pitch extraction algorithm, you need to download the RMVPE weights and place them in the RVC root directory
https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/rmvpe.pt
For AMD/Intel graphics cards users you need download:
https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/rmvpe.onnx
```
Intel ARC graphics cards users needs to run `source /opt/intel/oneapi/setvars.sh` command before starting Webui.
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.
## 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