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Merge pull request #1651 from everypizza1/patch-1

Fix: pdate README.en.md
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CONTRIBUTING.md Normal file
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# 贡献规则
1. 一般来说,作者`@RVC-Boss`将拒绝所有的算法更改,除非它是为了修复某个代码层面的错误或警告
2. 您可以贡献本仓库的其他位置如翻译和WebUI但请尽量作最小更改
3. 所有更改都需要由`@RVC-Boss`批准因此您的PR可能会被搁置
4. 由此带来的不便请您谅解
# Contributing Rules
1. Generally, the author `@RVC-Boss` will reject all algorithm changes unless what is to fix a code-level error or warning.
2. You can contribute to other parts of this repo like translations and WebUI, but please minimize your changes as much as possible.
3. All changes need to be approved by `@RVC-Boss`, so your PR may be put on hold.
4. Please accept our apologies for any inconvenience caused.

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@ -32,26 +32,25 @@ Realtime Voice Conversion GUIgo-realtime-gui.bat
![image](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/assets/129054828/143246a9-8b42-4dd1-a197-430ede4d15d7)
> The dataset for the pre-training model uses nearly 50 hours of high quality VCTK open source dataset.
> The dataset for the pre-training model uses nearly 50 hours of high quality audio from the 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.
> High quality licensed song datasets will be added to the training-set often for your use, without having to worry 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:
## 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.
+ Easy + fast training, even on poor graphics cards;
+ Training with a small amounts of data (>=10min low noise speech recommended);
+ Model fusion to change timbres (using ckpt processing tab->ckpt merge);
+ Easy-to-use WebUI;
+ UVR5 model to quickly separate vocals and instruments;
+ High-pitch Voice Extraction Algorithm [InterSpeech2023-RMVPE](#Credits) to prevent a muted sound problem. Provides the best results (significantly) and is faster with 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.
The following commands need to be executed with Python 3.8 or higher.
(Windows/Linux)
First install the main dependencies through pip:
@ -166,7 +165,7 @@ You might also need to set these environment variables (e.g. on a RX6700XT):
export ROCM_PATH=/opt/rocm
export HSA_OVERRIDE_GFX_VERSION=10.3.0
````
Also make sure your user is part of the `render` and `video` group:
Make sure your user is part of the `render` and `video` group:
````
sudo usermod -aG render $USERNAME
sudo usermod -aG video $USERNAME

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