Changelog | FAQ (Frequently Asked Questions)
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Check our Demo Video here!
Realtime Voice Conversion Software using RVC : 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 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:
# 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:
# 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:
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
:
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.
Here's a list of Pre-models and other files that RVC needs:
./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:
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
- VITS
- HIFIGAN
- Gradio
- FFmpeg
- Ultimate Vocal Remover
- audio-slicer
- Vocal pitch extraction:RMVPE