206 lines
8.4 KiB
Markdown
206 lines
8.4 KiB
Markdown
<div align="center">
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<h1>Retrieval-based-Voice-Conversion-WebUI</h1>
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一个基于VITS的简单易用的变声框架<br><br>
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[![madewithlove](https://img.shields.io/badge/made_with-%E2%9D%A4-red?style=for-the-badge&labelColor=orange
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)](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI)
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<img src="https://counter.seku.su/cmoe?name=rvc&theme=r34" /><br>
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[![Open In Colab](https://img.shields.io/badge/Colab-F9AB00?style=for-the-badge&logo=googlecolab&color=525252)](https://colab.research.google.com/github/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/Retrieval_based_Voice_Conversion_WebUI.ipynb)
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[![Licence](https://img.shields.io/badge/LICENSE-MIT-green.svg?style=for-the-badge)](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/LICENSE)
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[![Huggingface](https://img.shields.io/badge/🤗%20-Spaces-yellow.svg?style=for-the-badge)](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/)
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[![Discord](https://img.shields.io/badge/RVC%20Developers-Discord-7289DA?style=for-the-badge&logo=discord&logoColor=white)](https://discord.gg/HcsmBBGyVk)
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[**更新日志**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/docs/Changelog_CN.md) | [**常见问题解答**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98%E8%A7%A3%E7%AD%94) | [**AutoDL·5毛钱训练AI歌手**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/Autodl%E8%AE%AD%E7%BB%83RVC%C2%B7AI%E6%AD%8C%E6%89%8B%E6%95%99%E7%A8%8B) | [**对照实验记录**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/Autodl%E8%AE%AD%E7%BB%83RVC%C2%B7AI%E6%AD%8C%E6%89%8B%E6%95%99%E7%A8%8B](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/%E5%AF%B9%E7%85%A7%E5%AE%9E%E9%AA%8C%C2%B7%E5%AE%9E%E9%AA%8C%E8%AE%B0%E5%BD%95)) | [**在线演示**](https://modelscope.cn/studios/FlowerCry/RVCv2demo)
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[**English**](./docs/en/README.en.md) | [**中文简体**](./README.md) | [**日本語**](./docs/jp/README.ja.md) | [**한국어**](./docs/kr/README.ko.md) ([**韓國語**](./docs/kr/README.ko.han.md)) | [**Français**](./docs/fr/README.fr.md)| [**Türkçe**](./docs/tr/README.tr.md)
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</div>
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> 底模使用接近50小时的开源高质量VCTK训练集训练,无版权方面的顾虑,请大家放心使用
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> 请期待RVCv3的底模,参数更大,数据更大,效果更好,基本持平的推理速度,需要训练数据量更少。
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<table>
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<tr>
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<td align="center">训练推理界面</td>
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<td align="center">实时变声界面</td>
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</tr>
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<tr>
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<td align="center"><img src="https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/assets/129054828/092e5c12-0d49-4168-a590-0b0ef6a4f630"></td>
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<td align="center"><img src="https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/assets/129054828/730b4114-8805-44a1-ab1a-04668f3c30a6"></td>
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</tr>
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<tr>
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<td align="center">go-web.bat</td>
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<td align="center">go-realtime-gui.bat</td>
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</tr>
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<tr>
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<td align="center">可以自由选择想要执行的操作。</td>
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<td align="center">我们已经实现端到端170ms延迟。如使用ASIO输入输出设备,已能实现端到端90ms延迟,但非常依赖硬件驱动支持。</td>
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</tr>
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</table>
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## 简介
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本仓库具有以下特点
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+ 使用top1检索替换输入源特征为训练集特征来杜绝音色泄漏
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+ 即便在相对较差的显卡上也能快速训练
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+ 使用少量数据进行训练也能得到较好结果(推荐至少收集10分钟低底噪语音数据)
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+ 可以通过模型融合来改变音色(借助ckpt处理选项卡中的ckpt-merge)
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+ 简单易用的网页界面
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+ 可调用UVR5模型来快速分离人声和伴奏
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+ 使用最先进的[人声音高提取算法InterSpeech2023-RMVPE](#参考项目)根绝哑音问题。效果最好(显著地)但比crepe_full更快、资源占用更小
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+ A卡I卡加速支持
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点此查看我们的[演示视频](https://www.bilibili.com/video/BV1pm4y1z7Gm/) !
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## 环境配置
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以下指令需在 Python 版本大于3.8的环境中执行。
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### Windows/Linux/MacOS等平台通用方法
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下列方法任选其一。
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#### 1. 通过 pip 安装依赖
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1. 安装Pytorch及其核心依赖,若已安装则跳过。参考自: https://pytorch.org/get-started/locally/
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```bash
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pip install torch torchvision torchaudio
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```
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2. 如果是 win 系统 + Nvidia Ampere 架构(RTX30xx),根据 #21 的经验,需要指定 pytorch 对应的 cuda 版本
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```bash
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pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117
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```
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3. 根据自己的显卡安装对应依赖
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- N卡
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```bash
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pip install -r requirements.txt
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```
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- A卡/I卡
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```bash
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pip install -r requirements-dml.txt
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```
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- A卡ROCM(Linux)
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```bash
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pip install -r requirements-amd.txt
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```
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- I卡IPEX(Linux)
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```bash
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pip install -r requirements-ipex.txt
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```
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#### 2. 通过 poetry 来安装依赖
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安装 Poetry 依赖管理工具,若已安装则跳过。参考自: https://python-poetry.org/docs/#installation
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```bash
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curl -sSL https://install.python-poetry.org | python3 -
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```
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通过poetry安装依赖
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```bash
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poetry install
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```
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### MacOS
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可以通过 `run.sh` 来安装依赖
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```bash
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sh ./run.sh
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```
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## 其他预模型准备
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RVC需要其他一些预模型来推理和训练。
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你可以从我们的[Hugging Face space](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/)下载到这些模型。
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### 1. 下载 assets
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以下是一份清单,包括了所有RVC所需的预模型和其他文件的名称。你可以在`tools`文件夹找到下载它们的脚本。
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- ./assets/hubert/hubert_base.pt
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- ./assets/pretrained
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- ./assets/uvr5_weights
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想使用v2版本模型的话,需要额外下载
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- ./assets/pretrained_v2
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### 2. 安装 ffmpeg
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若ffmpeg和ffprobe已安装则跳过。
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#### Ubuntu/Debian 用户
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```bash
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sudo apt install ffmpeg
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```
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#### MacOS 用户
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```bash
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brew install ffmpeg
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```
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#### Windwos 用户
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下载后放置在根目录。
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- 下载[ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe)
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- 下载[ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe)
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### 3. 下载 rmvpe 人声音高提取算法所需文件
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如果你想使用最新的RMVPE人声音高提取算法,则你需要下载音高提取模型参数并放置于RVC根目录。
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- 下载[rmvpe.pt](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/rmvpe.pt)
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#### 下载 rmvpe 的 dml 环境(可选, A卡/I卡用户)
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- 下载[rmvpe.onnx](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/rmvpe.onnx)
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## 4. AMD显卡Rocm(可选, 仅Linux)
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如果你想基于AMD的Rocm技术在Linux系统上运行RVC,请先在[这里](https://rocm.docs.amd.com/en/latest/deploy/linux/os-native/install.html)安装所需的驱动。
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若你使用的是Arch Linux,可以使用pacman来安装所需驱动:
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````
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pacman -S rocm-hip-sdk rocm-opencl-sdk
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````
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对于某些型号的显卡,你可能需要额外配置如下的环境变量(如:RX6700XT):
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````
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export ROCM_PATH=/opt/rocm
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export HSA_OVERRIDE_GFX_VERSION=10.3.0
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````
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同时确保你的当前用户处于`render`与`video`用户组内:
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````
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sudo usermod -aG render $USERNAME
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sudo usermod -aG video $USERNAME
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````
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## 开始使用
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### 直接启动
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使用以下指令来启动 WebUI
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```bash
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python infer-web.py
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```
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### 使用整合包
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下载并解压`RVC-beta.7z`
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#### Windows 用户
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双击`go-web.bat`
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#### MacOS 用户
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```bash
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sh ./run.sh
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```
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### 对于需要使用IPEX技术的I卡用户(仅Linux)
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```bash
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source /opt/intel/oneapi/setvars.sh
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```
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仓库内还有一份[小白简易教程.doc](/docs/小白简易教程.doc)以供参考。
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## 参考项目
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+ [ContentVec](https://github.com/auspicious3000/contentvec/)
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+ [VITS](https://github.com/jaywalnut310/vits)
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+ [HIFIGAN](https://github.com/jik876/hifi-gan)
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+ [Gradio](https://github.com/gradio-app/gradio)
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+ [FFmpeg](https://github.com/FFmpeg/FFmpeg)
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+ [Ultimate Vocal Remover](https://github.com/Anjok07/ultimatevocalremovergui)
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+ [audio-slicer](https://github.com/openvpi/audio-slicer)
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+ [Vocal pitch extraction:RMVPE](https://github.com/Dream-High/RMVPE)
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+ The pretrained model is trained and tested by [yxlllc](https://github.com/yxlllc/RMVPE) and [RVC-Boss](https://github.com/RVC-Boss).
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## 感谢所有贡献者作出的努力
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<a href="https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/graphs/contributors" target="_blank">
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<img src="https://contrib.rocks/image?repo=RVC-Project/Retrieval-based-Voice-Conversion-WebUI" />
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</a>
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