[![Open In Colab](https://img.shields.io/badge/Colab-F9AB00?style=for-the-badge&logo=googlecolab&color=525252)](https://colab.research.google.com/github/liujing04/Retrieval-based-Voice-Conversion-WebUI/blob/main/Retrieval_based_Voice_Conversion_WebUI.ipynb)
> Realtime Voice Conversion Software using RVC : [w-okada/voice-changer](https://github.com/w-okada/voice-changer)
## Summary
This repository has the following features:
+ Reduce tone leakage by replacing 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.
+ The dataset for the pre-training model uses nearly 50 hours of high quality VCTK open source dataset, and high quality licensed song datasets will be added to training-set one after another for your use, without worrying about copyright infringement.
## Preparing the environment
We recommend you install the dependencies through poetry.
The following commands need to be executed in the environment of Python version 3.8 or higher:
```bash
# Install PyTorch-related core dependencies, skip if installed
#For Windows + Nvidia Ampere Architecture(RTX30xx), you need to specify the cuda version corresponding to pytorch according to the experience of https://github.com/liujing04/Retrieval-based-Voice-Conversion-WebUI/issues/21
**Notice**: `faiss 1.7.2` will raise Segmentation Fault: 11 under `MacOS`, please use `pip install faiss-cpu==1.7.0` if you use pip to install it manually.