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233 lines
9.0 KiB
Markdown
233 lines
9.0 KiB
Markdown
<div align="center">
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<h1>Retrieval-based-Voice-Conversion-WebUI</h1>
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简单易用的 语音音色转换/变声器 框架<br><br>
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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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[](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/LICENSE)
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[](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/)
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[**更新日志**](./docs/cn/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/%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) | [**Português**](./docs/pt/README.pt.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-webui.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，速度快、资源占用小
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+ A卡/I卡使用 CPU 依赖方案；Windows 可使用 DirectML，Linux 使用 CPU
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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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本分支面向 **Python 3.12 x64**，请先进入仓库根目录。Ubuntu 推荐使用 Ubuntu 24.04 x86_64。
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### Ubuntu 24.04
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```bash
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sudo apt update
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sudo apt install -y python3.12 python3.12-venv python3.12-dev ffmpeg unzip libsndfile1 libportaudio2
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python3.12 -m venv .venv
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source .venv/bin/activate
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python -m pip install --upgrade pip setuptools wheel
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```
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### Windows
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安装 Python 3.12 x64 后创建虚拟环境：
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```powershell
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py -3.12 -m venv .venv
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.venv\Scripts\activate
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python -m pip install --upgrade pip setuptools wheel
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```
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### 按硬件选择依赖
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| 硬件 | 安装方式 |
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| --- | --- |
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| CPU、AMD、Intel | 使用 `requirments_cpu_py312.txt`；Windows 可使用 DirectML，Linux 使用 CPU |
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| NVIDIA RTX 50 系 | 先安装 CUDA 12.8 版 Torch，再安装 `requirments_cu128_py312.txt` |
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| NVIDIA RTX 50 系以前 | 先安装 CUDA 11.8 版 Torch，再安装 `requirments_cu118_py312.txt` |
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#### CPU、AMD、Intel
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```bash
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python -m pip install -r requirments_cpu_py312.txt
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```
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#### NVIDIA RTX 50 系：两阶段安装
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```bash
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python -m pip install torch==2.7.1+cu128 torchaudio==2.7.1+cu128 \
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--index-url https://download.pytorch.org/whl/cu128 \
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--extra-index-url https://pypi.org/simple
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python -m pip install -r requirments_cu128_py312.txt
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```
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#### NVIDIA RTX 50 系以前：两阶段安装
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```bash
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python -m pip install torch==2.7.1+cu118 torchaudio==2.7.1+cu118 \
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--index-url https://download.pytorch.org/whl/cu118 \
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--extra-index-url https://pypi.org/simple
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python -m pip install -r requirments_cu118_py312.txt
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```
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检查 Torch 与 CUDA 状态：
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```bash
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python -c "import torch; print('torch:', torch.__version__); print('cuda:', torch.version.cuda); print('cuda available:', torch.cuda.is_available())"
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```
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### 修改下载源
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三个 `requirments_*.txt` 顶部已经包含下载源。中国大陆用户可保留默认镜像；需要使用官方源时，只替换 `--index-url` 和 `--extra-index-url`，保留包版本、CUDA 后缀和两阶段顺序。
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| Default mirror | Official source |
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| --- | --- |
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| `https://mirrors.pku.edu.cn/pypi/simple` | `https://pypi.org/simple` |
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| `https://mirrors.nju.edu.cn/pytorch/whl/cpu` | `https://download.pytorch.org/whl/cpu` |
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| `https://mirrors.nju.edu.cn/pytorch/whl/cu118` | `https://download.pytorch.org/whl/cu118` |
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| `https://mirrors.nju.edu.cn/pytorch/whl/cu128` | `https://download.pytorch.org/whl/cu128` |
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## 模型与运行目录
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WebUI 会自动创建运行目录。模型请从 [Hugging Face 模型仓库](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main) 下载，并保持以下路径：
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```text
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assets/
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├── hubert_base/
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│ ├── config.json
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│ ├── preprocessor_config.json
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│ └── pytorch_model.bin
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├── rmvpe/rmvpe.pt
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├── pretrained/
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├── pretrained_v2/
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├── uvr5_weights/
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├── weights/ # user RVC .pth models
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└── indices/ # user .index files
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logs/
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└── mute/ # training silence samples
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# Exact paths used by the code
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assets/hubert_base/config.json
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assets/hubert_base/preprocessor_config.json
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assets/hubert_base/pytorch_model.bin
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assets/rmvpe/rmvpe.pt
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assets/pretrained/*.pth
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assets/pretrained_v2/*.pth
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assets/uvr5_weights/*
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assets/weights/*.pth
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assets/indices/*.index
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logs/mute/*
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```
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### 下载模型
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```bash
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python -m pip install --upgrade huggingface_hub
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# Required for inference and feature extraction
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hf download lj1995/VoiceConversionWebUI --revision main \
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--include "hubert_base/*" --local-dir assets
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hf download lj1995/VoiceConversionWebUI rmvpe.pt --revision main \
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--local-dir assets/rmvpe
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# Required for v1/v2 training
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hf download lj1995/VoiceConversionWebUI --revision main \
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--include "pretrained/*" "pretrained_v2/*" --local-dir assets
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hf download lj1995/VoiceConversionWebUI mute.zip --revision main \
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--local-dir .model-downloads
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python -m zipfile -e .model-downloads/mute.zip logs
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# Required only for UVR5 vocal separation
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hf download lj1995/VoiceConversionWebUI --revision main \
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--include "uvr5_weights/*" --local-dir assets
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```
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仅 Windows AMD/Intel DirectML 环境还需要：
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```bash
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hf download lj1995/VoiceConversionWebUI rmvpe.onnx --revision main \
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--local-dir assets/rmvpe
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```
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### FFmpeg
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Ubuntu 已在前面的系统依赖命令中安装 FFmpeg。Windows 用户可把下面两个文件放到项目根目录：
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- [ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/ffmpeg.exe?download=true)
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- [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/ffprobe.exe?download=true)
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## 开始使用
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启动 WebUI：
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```bash
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python webui.py
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```
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无桌面的 Ubuntu 服务器：
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```bash
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python webui.py --noautoopen
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```
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默认服务监听端口为 `7865`。用户自己的 `.pth` 模型放入 `assets/weights/`，`.index` 文件放入 `assets/indices/`。
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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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