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diff --git a/README.md b/README.md
@@ -17,14 +17,6 @@ A Powerful Few-shot Voice Conversion and Text-to-Speech WebUI.<br><br>
 
 ---
 
-> Check out our [demo video](https://www.bilibili.com/video/BV12g4y1m7Uw) here!
-
-Unseen speakers few-shot fine-tuning demo:
-
-https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-80c060ab47fb
-
-For users in China region, you can use AutoDL Cloud Docker to experience the full functionality online: https://www.codewithgpu.com/i/RVC-Boss/GPT-SoVITS/GPT-SoVITS-Official
-
 ## Features:
 
 1. **Zero-shot TTS:** Input a 5-second vocal sample and experience instant text-to-speech conversion.
@@ -35,35 +27,67 @@ For users in China region, you can use AutoDL Cloud Docker to experience the ful
 
 4. **WebUI Tools:** Integrated tools include voice accompaniment separation, automatic training set segmentation, Chinese ASR, and text labeling, assisting beginners in creating training datasets and GPT/SoVITS models.
 
-## Environment Preparation
+**Check out our [demo video](https://www.bilibili.com/video/BV12g4y1m7Uw) here!**
+
+Unseen speakers few-shot fine-tuning demo:
+
+https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-80c060ab47fb
+
+## Installation
 
-If you are a Windows user (tested with win>=10) you can install directly via the prezip. Just download the [prezip](https://huggingface.co/lj1995/GPT-SoVITS-windows-package/resolve/main/GPT-SoVITS-beta.7z?download=true), unzip it and double-click go-webui.bat to start GPT-SoVITS-WebUI.
+For users in China region, you can [click here](https://www.codewithgpu.com/i/RVC-Boss/GPT-SoVITS/GPT-SoVITS-Official) to use AutoDL Cloud Docker to experience the full functionality online.
 
 ### Tested Environments
 
 - Python 3.9, PyTorch 2.0.1, CUDA 11
 - Python 3.10.13, PyTorch 2.1.2, CUDA 12.3
-- Python 3.9, PyTorch 2.3.0.dev20240122, macOS 14.3 (Apple silicon, GPU)
+- Python 3.9, PyTorch 2.3.0.dev20240122, macOS 14.3 (Apple silicon)
 
-_Note: numba==0.56.4 require py<3.11_
+_Note: numba==0.56.4 requires py<3.11_
 
-### Quick Install with Conda
+### Windows
+
+If you are a Windows user (tested with win>=10), you can directly download the [pre-packaged distribution](https://huggingface.co/lj1995/GPT-SoVITS-windows-package/resolve/main/GPT-SoVITS-beta.7z?download=true) and double-click on _go-webui.bat_ to start GPT-SoVITS-WebUI.
+
+### Linux
 
 ```bash
 conda create -n GPTSoVits python=3.9
 conda activate GPTSoVits
 bash install.sh
 ```
 
+### macOS
+
+Only Macs that meet the following conditions can train models:
+
+- Mac computers with Apple silicon
+- macOS 12.3 or later
+- Xcode command-line tools installed by running `xcode-select --install`
+
+**All Macs can do inference with CPU, which has been demonstrated to outperform GPU inference.**
+
+First make sure you have installed FFmpeg by running `brew install ffmpeg` or `conda install ffmpeg`, then install by using the following commands:
+
+```bash
+conda create -n GPTSoVits python=3.9
+conda activate GPTSoVits
+
+pip3 install --pre torch torchaudio --index-url https://download.pytorch.org/whl/nightly/cpu
+pip install -r requirements.txt
+```
+
+_Note: Training models will only work if you've installed PyTorch Nightly._
+
 ### Install Manually
 
-#### Pip Packages
+#### Install Dependences
 
 ```bash
 pip install -r requirements.txt
 ```
 
-#### FFmpeg
+#### Install FFmpeg
 
 ##### Conda Users
 
@@ -79,57 +103,10 @@ sudo apt install libsox-dev
 conda install -c conda-forge 'ffmpeg<7'
 ```
 
-##### MacOS Users
-
-```bash
-brew install ffmpeg
-```
-
 ##### Windows Users
 
 Download and place [ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe) and [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe) in the GPT-SoVITS root.
 
-### Pretrained Models
-
-Download pretrained models from [GPT-SoVITS Models](https://huggingface.co/lj1995/GPT-SoVITS) and place them in `GPT_SoVITS/pretrained_models`.
-
-For UVR5 (Vocals/Accompaniment Separation & Reverberation Removal, additionally), download models from [UVR5 Weights](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/uvr5_weights) and place them in `tools/uvr5/uvr5_weights`.
-
-Users in China region can download these two models by entering the links below and clicking "Download a copy"
-
-- [GPT-SoVITS Models](https://www.icloud.com.cn/iclouddrive/056y_Xog_HXpALuVUjscIwTtg#GPT-SoVITS_Models)
-
-- [UVR5 Weights](https://www.icloud.com.cn/iclouddrive/0bekRKDiJXboFhbfm3lM2fVbA#UVR5_Weights)
-
-For Chinese ASR (additionally), download models from [Damo ASR Model](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/files), [Damo VAD Model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/files), and [Damo Punc Model](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/files) and place them in `tools/damo_asr/models`.
-
-### For Mac Users
-
-If you are a Mac user, make sure you meet the following conditions for training and inferencing with GPU:
-
-- Mac computers with Apple silicon
-- macOS 12.3 or later
-- Xcode command-line tools installed by running `xcode-select --install`
-
-_Other Macs can do inference with CPU only._
-
-Then install by using the following commands:
-
-#### Create Environment
-
-```bash
-conda create -n GPTSoVits python=3.9
-conda activate GPTSoVits
-```
-
-#### Install Requirements
-
-```bash
-pip install -r requirements.txt
-pip uninstall torch torchaudio
-pip3 install --pre torch torchaudio --index-url https://download.pytorch.org/whl/nightly/cpu
-```
-
 ### Using Docker
 
 #### docker-compose.yaml configuration
@@ -157,6 +134,20 @@ As above, modify the corresponding parameters based on your actual situation, th
 docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-DockerTest\output:/workspace/output --volume=G:\GPT-SoVITS-DockerTest\logs:/workspace/logs --volume=G:\GPT-SoVITS-DockerTest\SoVITS_weights:/workspace/SoVITS_weights --workdir=/workspace -p 9880:9880 -p 9871:9871 -p 9872:9872 -p 9873:9873 -p 9874:9874 --shm-size="16G" -d breakstring/gpt-sovits:xxxxx
 ```
 
+## Pretrained Models
+
+Download pretrained models from [GPT-SoVITS Models](https://huggingface.co/lj1995/GPT-SoVITS) and place them in `GPT_SoVITS/pretrained_models`.
+
+For UVR5 (Vocals/Accompaniment Separation & Reverberation Removal, additionally), download models from [UVR5 Weights](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/uvr5_weights) and place them in `tools/uvr5/uvr5_weights`.
+
+Users in China region can download these two models by entering the links below and clicking "Download a copy"
+
+- [GPT-SoVITS Models](https://www.icloud.com.cn/iclouddrive/056y_Xog_HXpALuVUjscIwTtg#GPT-SoVITS_Models)
+
+- [UVR5 Weights](https://www.icloud.com.cn/iclouddrive/0bekRKDiJXboFhbfm3lM2fVbA#UVR5_Weights)
+
+For Chinese ASR (additionally), download models from [Damo ASR Model](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/files), [Damo VAD Model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/files), and [Damo Punc Model](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/files) and place them in `tools/damo_asr/models`.
+
 ## Dataset Format
 
 The TTS annotation .list file format:
@@ -229,8 +220,6 @@ python ./tools/damo_asr/WhisperASR.py -i <input> -o <output> -f <file_name.list>
 A custom list save path is enabled
 ## Credits
 
-
-
 Special thanks to the following projects and contributors:
 
 - [ar-vits](https://github.com/innnky/ar-vits)

diff --git a/docs/cn/README.md b/docs/cn/README.md
@@ -17,12 +17,6 @@
 
 ---
 
-> 查看我们的介绍视频 [demo video](https://www.bilibili.com/video/BV12g4y1m7Uw)
-
-https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-80c060ab47fb
-
-中国地区用户可使用 AutoDL 云端镜像进行体验：https://www.codewithgpu.com/i/RVC-Boss/GPT-SoVITS/GPT-SoVITS-Official
-
 ## 功能：
 
 1. **零样本文本到语音（TTS）：** 输入 5 秒的声音样本，即刻体验文本到语音转换。
@@ -33,62 +27,67 @@ https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-
 
 4. **WebUI 工具：** 集成工具包括声音伴奏分离、自动训练集分割、中文自动语音识别(ASR)和文本标注，协助初学者创建训练数据集和 GPT/SoVITS 模型。
 
-## 环境准备
+**查看我们的介绍视频 [demo video](https://www.bilibili.com/video/BV12g4y1m7Uw)**
 
-如果你是 Windows 用户（已在 win>=10 上测试），可以直接通过预打包文件安装。只需下载[预打包文件](https://huggingface.co/lj1995/GPT-SoVITS-windows-package/resolve/main/GPT-SoVITS-beta.7z?download=true)，解压后双击 go-webui.bat 即可启动 GPT-SoVITS-WebUI。
+未见过的说话者 few-shot 微调演示：
 
-### 测试通过的 Python 和 PyTorch 版本
+https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-80c060ab47fb
 
-- Python 3.9、PyTorch 2.0.1 和 CUDA 11
-- Python 3.10.13, PyTorch 2.1.2 和 CUDA 12.3
-- Python 3.9、Pytorch 2.3.0.dev20240122 和 macOS 14.3（Apple 芯片，GPU）
+## 安装
 
-_注意: numba==0.56.4 需要 python<3.11_
+中国地区用户可[点击此处](https://www.codewithgpu.com/i/RVC-Boss/GPT-SoVITS/GPT-SoVITS-Official)使用 AutoDL 云端镜像进行体验。
 
-### Mac 用户
+### 测试通过的环境
 
-如果你是 Mac 用户，请先确保满足以下条件以使用 GPU 进行训练和推理：
+- Python 3.9、PyTorch 2.0.1 和 CUDA 11
+- Python 3.10.13, PyTorch 2.1.2 和 CUDA 12.3
+- Python 3.9、Pytorch 2.3.0.dev20240122 和 macOS 14.3（Apple 芯片）
 
-- 搭载 Apple 芯片的 Mac
-- macOS 12.3 或更高版本
-- 已通过运行`xcode-select --install`安装 Xcode command-line tools
+_注意: numba==0.56.4 需要 python<3.11_
 
-_其他 Mac 仅支持使用 CPU 进行推理_
+### Windows
 
-然后使用以下命令安装：
+如果你是 Windows 用户（已在 win>=10 上测试），可以直接下载[预打包文件](https://huggingface.co/lj1995/GPT-SoVITS-windows-package/resolve/main/GPT-SoVITS-beta.7z?download=true)，解压后双击 go-webui.bat 即可启动 GPT-SoVITS-WebUI。
 
-#### 创建环境
+### Linux
 
 ```bash
 conda create -n GPTSoVits python=3.9
 conda activate GPTSoVits
+bash install.sh
 ```
 
-#### 安装依赖
+### macOS
 
-```bash
-pip install -r requirements.txt
-pip uninstall torch torchaudio
-pip3 install --pre torch torchaudio --index-url https://download.pytorch.org/whl/nightly/cpu
-```
+只有符合以下条件的 Mac 可以训练模型：
+
+- 搭载 Apple 芯片的 Mac
+- 运行macOS 12.3 或更高版本
+- 已通过运行`xcode-select --install`安装 Xcode command-line tools
+
+**所有 Mac 都可使用 CPU 进行推理，且已测试性能优于 GPU。**
 
-### 使用 Conda 快速安装
+首先确保你已通过运行 `brew install ffmpeg` 或 `conda install ffmpeg` 安装 FFmpeg，然后运行以下命令安装：
 
 ```bash
 conda create -n GPTSoVits python=3.9
 conda activate GPTSoVits
-bash install.sh
+
+pip3 install --pre torch torchaudio --index-url https://download.pytorch.org/whl/nightly/cpu
+pip install -r requirements.txt
 ```
 
-### 手动安装包
+_注：只有安装了Pytorch Nightly才可训练模型。_
 
-#### Pip 包
+### 手动安装
+
+#### 安装依赖
 
 ```bash
 pip install -r requirements.txt
 ```
 
-#### FFmpeg
+#### 安装 FFmpeg
 
 ##### Conda 使用者
 
@@ -104,12 +103,6 @@ sudo apt install libsox-dev
 conda install -c conda-forge 'ffmpeg<7'
 ```
 
-##### MacOS 使用者
-
-```bash
-brew install ffmpeg
-```
-
 ##### Windows 使用者
 
 下载并将 [ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe) 和 [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe) 放置在 GPT-SoVITS 根目录下。
@@ -141,19 +134,19 @@ docker compose -f "docker-compose.yaml" up -d
 docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-DockerTest\output:/workspace/output --volume=G:\GPT-SoVITS-DockerTest\logs:/workspace/logs --volume=G:\GPT-SoVITS-DockerTest\SoVITS_weights:/workspace/SoVITS_weights --workdir=/workspace -p 9880:9880 -p 9871:9871 -p 9872:9872 -p 9873:9873 -p 9874:9874 --shm-size="16G" -d breakstring/gpt-sovits:xxxxx
 ```
 
-### 预训练模型
+## 预训练模型
 
 从 [GPT-SoVITS Models](https://huggingface.co/lj1995/GPT-SoVITS) 下载预训练模型，并将它们放置在 `GPT_SoVITS\pretrained_models` 中。
 
-对于 UVR5（人声/伴奏分离和混响移除，另外），从 [UVR5 Weights](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/uvr5_weights) 下载模型，并将它们放置在 `tools/uvr5/uvr5_weights` 中。
+对于 UVR5（人声/伴奏分离和混响移除，附加），从 [UVR5 Weights](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/uvr5_weights) 下载模型，并将它们放置在 `tools/uvr5/uvr5_weights` 中。
 
 中国地区用户可以进入以下链接并点击“下载副本”下载以上两个模型：
 
 - [GPT-SoVITS Models](https://www.icloud.com.cn/iclouddrive/056y_Xog_HXpALuVUjscIwTtg#GPT-SoVITS_Models)
 
 - [UVR5 Weights](https://www.icloud.com.cn/iclouddrive/0bekRKDiJXboFhbfm3lM2fVbA#UVR5_Weights)
 
-对于中文自动语音识别（另外），从 [Damo ASR Model](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/files), [Damo VAD Model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/files), 和 [Damo Punc Model](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/files) 下载模型，并将它们放置在 `tools/damo_asr/models` 中。
+对于中文自动语音识别（附加），从 [Damo ASR Model](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/files), [Damo VAD Model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/files), 和 [Damo Punc Model](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/files) 下载模型，并将它们放置在 `tools/damo_asr/models` 中。
 
 ## 数据集格式