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fcyai
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003d053
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Parent(s):
4dd22f9
init
Browse files- ApiTest.html +99 -0
- README.md +121 -13
- abc/.gitignore +163 -0
- abc/LICENSE +157 -0
- abc/README.md +131 -0
- abc/README_CN.md +133 -0
- abc/infer.ipynb +0 -0
- abc/requirements.txt +7 -0
- api.py +361 -0
- assets/shot1.png +0 -0
- assets/shot2.png +0 -0
- assets/shot3.png +0 -0
- chattts_webui_mix.ipynb +65 -0
- cli.py +24 -0
- config.py +46 -0
- llm_utils.py +119 -0
- requirements-macos.txt +97 -0
- requirements.txt +4 -0
- slct_voice_240605.json +0 -0
- tts_model.py +175 -0
- utils.py +333 -0
- webui_mix.py +1036 -0
- zh_normalization/README.md +16 -0
- zh_normalization/__init__.py +14 -0
- zh_normalization/char_convert.py +46 -0
- zh_normalization/chronology.py +134 -0
- zh_normalization/constants.py +62 -0
- zh_normalization/num.py +238 -0
- zh_normalization/phonecode.py +63 -0
- zh_normalization/quantifier.py +63 -0
- zh_normalization/text_normlization.py +154 -0
ApiTest.html
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<!DOCTYPE html>
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<html lang="zh-CN">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>TTS 测试</title>
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<style>
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body {
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font-family: Arial, sans-serif;
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margin: 20px;
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max-width: 600px;
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margin: auto;
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}
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label, button {
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display: block;
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margin-top: 10px;
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}
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textarea, select, input[type="number"], input[type="text"] {
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width: calc(100% - 10px);
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margin-top: 5px;
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padding: 5px;
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font-size: 16px;
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}
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button {
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width: 100%;
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padding: 10px;
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background-color: #4CAF50;
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color: white;
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border: none;
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font-size: 16px;
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cursor: pointer;
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}
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button:hover {
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background-color: #45a049;
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}
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h2, pre {
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margin-top: 20px;
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}
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audio {
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width: 100%;
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margin-top: 10px;
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}
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</style>
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</head>
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<body>
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<h1>ChatTTS API 测试</h1>
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<label for="api_url">接口 URL：</label>
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<input type="text" id="api_url" value="http://localhost:9880/">
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<label for="text">测试文本：</label>
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<textarea id="text" rows="10">我是一个充满活力的人，喜欢运动，喜欢旅行，喜欢尝试新鲜事物。我喜欢挑战自己，不断突破自己的极限，让自己变得更加强大。我是一个充满活力的人，喜欢运动，喜欢旅行，喜欢尝试新鲜事物。我喜欢挑战自己，不断突破自己的极限，让自己变得更加强大。</textarea>
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<label for="media_type">媒体类型：</label>
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<select id="media_type">
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<option value="wav">wav</option>
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<option value="mp3">mp3</option>
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<option value="flac">flac</option>
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</select>
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<label for="seed">种子：</label>
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<input type="number" id="seed" value="2581">
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<label for="streaming">流式输出：</label>
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<input type="checkbox" id="streaming" checked>
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<button onclick="sendRequest()">发送请求</button>
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<h2>输出</h2>
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<pre id="output"></pre>
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<audio id="audio" controls></audio>
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<script>
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async function sendRequest() {
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const apiUrl = document.getElementById('api_url').value;
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const text = document.getElementById('text').value;
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const media_type = document.getElementById('media_type').value;
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const seed = document.getElementById('seed').value;
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const streaming = document.getElementById('streaming').checked ? 1 : 0;
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const output = document.getElementById('output');
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output.textContent = "请求中...\n";
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const audioElement = document.getElementById('audio');
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try {
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const url = `${apiUrl}?text=${encodeURIComponent(text)}&media_type=${media_type}&seed=${seed}&streaming=${streaming}`;
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output.textContent += `请求 URL: ${url}\n`;
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audioElement.src = url;
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audioElement.play();
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output.textContent += "音频即将播放...\n";
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} catch (error) {
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output.textContent += `请求错误: ${error}\n`;
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}
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}
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</script>
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</body>
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</html>
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README.md
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# ChatTTS_colab
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🚀 一键部署（含win离线整合包）！基于 [ChatTTS](https://github.com/2noise/ChatTTS) ，支持音色抽卡、长音频生成和分角色朗读。简单易用，无需复杂安装。。
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**🏆 2000条说话人音色库已开源 🏆** 项目地址： [ChatTTS_Speaker](https://github.com/6drf21e/ChatTTS_Speaker)
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> 支持按男女、年龄、特征查找稳定音色。
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# 下载地址
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| 版本 | 地址 | 介绍 |
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|----------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------|
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| 在线Colab版 | [](https://colab.research.google.com/github/6drf21e/ChatTTS_colab/blob/main/chattts_webui_mix.ipynb) | 可以在 Google Colab 上一键运行，需要 Google账号，Colab 自带15GB的GPU |
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| 离线整合版 | [百度网盘](https://pan.baidu.com/s/1-hGiPLs6ORM8sZv0xTdxFA?pwd=h3c5) 提取码: h3c5 | 下载本地运行，支持 GPU/CPU，适用 Windows 10 及以上 |
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| 离线整合版 | [夸克网盘](https://pan.quark.cn/s/c963e147f204) | 下载本地运行，支持 GPU/CPU，适用 Windows 10 及以上 |
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# 演示视频
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[](https://www.youtube.com/watch?v=199fyU7NfUQ)
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欢迎关注 [氪学家频道](https://www.youtube.com/@kexue) ，获取更多有趣的科技视频。
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## 特点
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- **Colab 一键运行**：无需复杂的环境配置，只需点击上方的 Colab 按钮，即可在浏览器中直接运行项目。
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- **音色抽卡功能**：批量生成多个音色，并可保存自己喜欢的音色。
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- **支持生成长音频**：适合生成较长的语音内容。
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- **字符处理**：对数字和朗读错误的标点做了初步处理。
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- **分角色朗读功能** ：支持对不同角色的文本进行分角色朗读，并支持大模型一键生产脚本。
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## 功能展示
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### 分角色朗读功能
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### 音色抽卡功能
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### 支持生成长音频
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## 快速开始
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### 在 Colab 运行
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1. 点击最上方的 "Open In Colab" 按钮，打开 Colab 笔记本。
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2. 点击菜单栏的–代码执行程序–全部运行即可
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3. 执行后在下方的日志中找到类似
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Running on public URL: https://**********.gradio.live
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4. https://**********.gradio.live 就是可以访问的公网地址
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### 在 macOS 上运行
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1. 安装 [Conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/macos.html)（如果尚未安装）。
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2. 打开终端，创建一个新的 conda 环境：
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```bash
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conda create -n "ChatTTS_colab" python=3.11
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```
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3. 激活刚创建的环境：
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```bash
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conda activate ChatTTS_colab
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```
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3. 克隆本项目仓库到本地：
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```bash
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git clone git@github.com:6drf21e/ChatTTS_colab.git
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```
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4. 手动安装 ChatTTS 依赖到项目目录：
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```bash
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cd ChatTTS_colab
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git clone https://github.com/2noise/ChatTTS
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cd ChatTTS
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git checkout -q f4c8329
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cd ..
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mv ChatTTS temp
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mv temp/ChatTTS ./ChatTTS
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rm -rf temp
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```
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5. 在项目目录安装 ChatTTS_colab 所需的依赖：
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```bash
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pip install -r requirements-macos.txt
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```
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6. 运行项目，等待自动下载模型：
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```bash
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python webui_mix.py
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# Loading ChatTTS model...
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```
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一切正常的话会自动打开浏览器。
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## 常见问题：
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1. 第一次运行项目，ChatTTS 会自动从 huggingface 下载模型，如果因为网络问题下载失败，那么 ChatTTS 是无法自行重新下载的，需要清除缓存后重新触发下载。
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错误信息示例：
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```log
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FileNotFoundError: [Errno 2] No such file or directory: '~/.cache/huggingface/hub/models--2Noise--ChatTTS/snapshots/d7474137acb4f988874e5d57ad88d81bcb7e10b6/asset/Vocos.pt'
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```
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清除缓存的方法：
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```bash
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rm -rf ~/.cache/huggingface/hub/models--2Noise--ChatTTS
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```
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清除缓存后，再次执行 `python webui_mix.py`，就会重新下载模型。
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如果多次下载都无法成功，可以手动将**离线包**里的 models 拷贝到项目目录，从本地加载模型
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```bash
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python webui_mix.py --source local --local_path models
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```
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2. 如果下载模型速度慢，建议使用赛博活菩萨 [@padeoe](https://github.com/padeoe) 的镜像加速 https://hf-mirror.com/
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```bash
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export HF_ENDPOINT=https://hf-mirror.com
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```
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## 贡献
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欢迎对本项目提出建议或贡献代码。请通过 GitHub Issues 提出问题，或提交 Pull Request。
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## 许可证
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| 119 |
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本项目使用 MIT 许可证。
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abc/.gitignore
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|
| 1 |
+
# Byte-compiled / optimized / DLL files
|
| 2 |
+
__pycache__/
|
| 3 |
+
*.py[cod]
|
| 4 |
+
*$py.class
|
| 5 |
+
*.ckpt
|
| 6 |
+
# C extensions
|
| 7 |
+
*.so
|
| 8 |
+
*.pt
|
| 9 |
+
|
| 10 |
+
# Distribution / packaging
|
| 11 |
+
.Python
|
| 12 |
+
outputs/
|
| 13 |
+
build/
|
| 14 |
+
develop-eggs/
|
| 15 |
+
dist/
|
| 16 |
+
downloads/
|
| 17 |
+
eggs/
|
| 18 |
+
.eggs/
|
| 19 |
+
lib/
|
| 20 |
+
lib64/
|
| 21 |
+
parts/
|
| 22 |
+
sdist/
|
| 23 |
+
var/
|
| 24 |
+
wheels/
|
| 25 |
+
share/python-wheels/
|
| 26 |
+
*.egg-info/
|
| 27 |
+
asset/*
|
| 28 |
+
.installed.cfg
|
| 29 |
+
*.egg
|
| 30 |
+
MANIFEST
|
| 31 |
+
|
| 32 |
+
# PyInstaller
|
| 33 |
+
# Usually these files are written by a python script from a template
|
| 34 |
+
# before PyInstaller builds the exe, so as to inject date/other infos into it.
|
| 35 |
+
*.manifest
|
| 36 |
+
*.spec
|
| 37 |
+
|
| 38 |
+
# Installer logs
|
| 39 |
+
pip-log.txt
|
| 40 |
+
pip-delete-this-directory.txt
|
| 41 |
+
|
| 42 |
+
# Unit test / coverage reports
|
| 43 |
+
htmlcov/
|
| 44 |
+
.tox/
|
| 45 |
+
.nox/
|
| 46 |
+
.coverage
|
| 47 |
+
.coverage.*
|
| 48 |
+
.cache
|
| 49 |
+
nosetests.xml
|
| 50 |
+
coverage.xml
|
| 51 |
+
*.cover
|
| 52 |
+
*.py,cover
|
| 53 |
+
.hypothesis/
|
| 54 |
+
.pytest_cache/
|
| 55 |
+
cover/
|
| 56 |
+
|
| 57 |
+
# Translations
|
| 58 |
+
*.mo
|
| 59 |
+
*.pot
|
| 60 |
+
|
| 61 |
+
# Django stuff:
|
| 62 |
+
*.log
|
| 63 |
+
local_settings.py
|
| 64 |
+
db.sqlite3
|
| 65 |
+
db.sqlite3-journal
|
| 66 |
+
|
| 67 |
+
# Flask stuff:
|
| 68 |
+
instance/
|
| 69 |
+
.webassets-cache
|
| 70 |
+
|
| 71 |
+
# Scrapy stuff:
|
| 72 |
+
.scrapy
|
| 73 |
+
|
| 74 |
+
# Sphinx documentation
|
| 75 |
+
docs/_build/
|
| 76 |
+
|
| 77 |
+
# PyBuilder
|
| 78 |
+
.pybuilder/
|
| 79 |
+
target/
|
| 80 |
+
|
| 81 |
+
# Jupyter Notebook
|
| 82 |
+
.ipynb_checkpoints
|
| 83 |
+
|
| 84 |
+
# IPython
|
| 85 |
+
profile_default/
|
| 86 |
+
ipython_config.py
|
| 87 |
+
|
| 88 |
+
# pyenv
|
| 89 |
+
# For a library or package, you might want to ignore these files since the code is
|
| 90 |
+
# intended to run in multiple environments; otherwise, check them in:
|
| 91 |
+
# .python-version
|
| 92 |
+
|
| 93 |
+
# pipenv
|
| 94 |
+
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
|
| 95 |
+
# However, in case of collaboration, if having platform-specific dependencies or dependencies
|
| 96 |
+
# having no cross-platform support, pipenv may install dependencies that don't work, or not
|
| 97 |
+
# install all needed dependencies.
|
| 98 |
+
#Pipfile.lock
|
| 99 |
+
|
| 100 |
+
# poetry
|
| 101 |
+
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
|
| 102 |
+
# This is especially recommended for binary packages to ensure reproducibility, and is more
|
| 103 |
+
# commonly ignored for libraries.
|
| 104 |
+
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
|
| 105 |
+
#poetry.lock
|
| 106 |
+
|
| 107 |
+
# pdm
|
| 108 |
+
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
|
| 109 |
+
#pdm.lock
|
| 110 |
+
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
|
| 111 |
+
# in version control.
|
| 112 |
+
# https://pdm.fming.dev/#use-with-ide
|
| 113 |
+
.pdm.toml
|
| 114 |
+
|
| 115 |
+
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
|
| 116 |
+
__pypackages__/
|
| 117 |
+
|
| 118 |
+
# Celery stuff
|
| 119 |
+
celerybeat-schedule
|
| 120 |
+
celerybeat.pid
|
| 121 |
+
|
| 122 |
+
# SageMath parsed files
|
| 123 |
+
*.sage.py
|
| 124 |
+
|
| 125 |
+
# Environments
|
| 126 |
+
.env
|
| 127 |
+
.venv
|
| 128 |
+
env/
|
| 129 |
+
venv/
|
| 130 |
+
ENV/
|
| 131 |
+
env.bak/
|
| 132 |
+
venv.bak/
|
| 133 |
+
|
| 134 |
+
# Spyder project settings
|
| 135 |
+
.spyderproject
|
| 136 |
+
.spyproject
|
| 137 |
+
|
| 138 |
+
# Rope project settings
|
| 139 |
+
.ropeproject
|
| 140 |
+
|
| 141 |
+
# mkdocs documentation
|
| 142 |
+
/site
|
| 143 |
+
|
| 144 |
+
# mypy
|
| 145 |
+
.mypy_cache/
|
| 146 |
+
.dmypy.json
|
| 147 |
+
dmypy.json
|
| 148 |
+
|
| 149 |
+
# Pyre type checker
|
| 150 |
+
.pyre/
|
| 151 |
+
|
| 152 |
+
# pytype static type analyzer
|
| 153 |
+
.pytype/
|
| 154 |
+
|
| 155 |
+
# Cython debug symbols
|
| 156 |
+
cython_debug/
|
| 157 |
+
|
| 158 |
+
# PyCharm
|
| 159 |
+
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
|
| 160 |
+
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
|
| 161 |
+
# and can be added to the global gitignore or merged into this file. For a more nuclear
|
| 162 |
+
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
|
| 163 |
+
#.idea/
|
abc/LICENSE
ADDED
|
@@ -0,0 +1,157 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
| 1 |
+
# Attribution-NonCommercial-NoDerivatives 4.0 International
|
| 2 |
+
|
| 3 |
+
> *Creative Commons Corporation (“Creative Commons”) is not a law firm and does not provide legal services or legal advice. Distribution of Creative Commons public licenses does not create a lawyer-client or other relationship. Creative Commons makes its licenses and related information available on an “as-is” basis. Creative Commons gives no warranties regarding its licenses, any material licensed under their terms and conditions, or any related information. Creative Commons disclaims all liability for damages resulting from their use to the fullest extent possible.*
|
| 4 |
+
>
|
| 5 |
+
> ### Using Creative Commons Public Licenses
|
| 6 |
+
>
|
| 7 |
+
> Creative Commons public licenses provide a standard set of terms and conditions that creators and other rights holders may use to share original works of authorship and other material subject to copyright and certain other rights specified in the public license below. The following considerations are for informational purposes only, are not exhaustive, and do not form part of our licenses.
|
| 8 |
+
>
|
| 9 |
+
> * __Considerations for licensors:__ Our public licenses are intended for use by those authorized to give the public permission to use material in ways otherwise restricted by copyright and certain other rights. Our licenses are irrevocable. Licensors should read and understand the terms and conditions of the license they choose before applying it. Licensors should also secure all rights necessary before applying our licenses so that the public can reuse the material as expected. Licensors should clearly mark any material not subject to the license. This includes other CC-licensed material, or material used under an exception or limitation to copyright. [More considerations for licensors](http://wiki.creativecommons.org/Considerations_for_licensors_and_licensees#Considerations_for_licensors).
|
| 10 |
+
>
|
| 11 |
+
> * __Considerations for the public:__ By using one of our public licenses, a licensor grants the public permission to use the licensed material under specified terms and conditions. If the licensor’s permission is not necessary for any reason–for example, because of any applicable exception or limitation to copyright–then that use is not regulated by the license. Our licenses grant only permissions under copyright and certain other rights that a licensor has authority to grant. Use of the licensed material may still be restricted for other reasons, including because others have copyright or other rights in the material. A licensor may make special requests, such as asking that all changes be marked or described. Although not required by our licenses, you are encouraged to respect those requests where reasonable. [More considerations for the public](http://wiki.creativecommons.org/Considerations_for_licensors_and_licensees#Considerations_for_licensees).
|
| 12 |
+
|
| 13 |
+
## Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License
|
| 14 |
+
|
| 15 |
+
By exercising the Licensed Rights (defined below), You accept and agree to be bound by the terms and conditions of this Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License ("Public License"). To the extent this Public License may be interpreted as a contract, You are granted the Licensed Rights in consideration of Your acceptance of these terms and conditions, and the Licensor grants You such rights in consideration of benefits the Licensor receives from making the Licensed Material available under these terms and conditions.
|
| 16 |
+
|
| 17 |
+
### Section 1 – Definitions.
|
| 18 |
+
|
| 19 |
+
a. __Adapted Material__ means material subject to Copyright and Similar Rights that is derived from or based upon the Licensed Material and in which the Licensed Material is translated, altered, arranged, transformed, or otherwise modified in a manner requiring permission under the Copyright and Similar Rights held by the Licensor. For purposes of this Public License, where the Licensed Material is a musical work, performance, or sound recording, Adapted Material is always produced where the Licensed Material is synched in timed relation with a moving image.
|
| 20 |
+
|
| 21 |
+
b. __Copyright and Similar Rights__ means copyright and/or similar rights closely related to copyright including, without limitation, performance, broadcast, sound recording, and Sui Generis Database Rights, without regard to how the rights are labeled or categorized. For purposes of this Public License, the rights specified in Section 2(b)(1)-(2) are not Copyright and Similar Rights.
|
| 22 |
+
|
| 23 |
+
e. __Effective Technological Measures__ means those measures that, in the absence of proper authority, may not be circumvented under laws fulfilling obligations under Article 11 of the WIPO Copyright Treaty adopted on December 20, 1996, and/or similar international agreements.
|
| 24 |
+
|
| 25 |
+
f. __Exceptions and Limitations__ means fair use, fair dealing, and/or any other exception or limitation to Copyright and Similar Rights that applies to Your use of the Licensed Material.
|
| 26 |
+
|
| 27 |
+
h. __Licensed Material__ means the artistic or literary work, database, or other material to which the Licensor applied this Public License.
|
| 28 |
+
|
| 29 |
+
i. __Licensed Rights__ means the rights granted to You subject to the terms and conditions of this Public License, which are limited to all Copyright and Similar Rights that apply to Your use of the Licensed Material and that the Licensor has authority to license.
|
| 30 |
+
|
| 31 |
+
h. __Licensor__ means the individual(s) or entity(ies) granting rights under this Public License.
|
| 32 |
+
|
| 33 |
+
i. __NonCommercial__ means not primarily intended for or directed towards commercial advantage or monetary compensation. For purposes of this Public License, the exchange of the Licensed Material for other material subject to Copyright and Similar Rights by digital file-sharing or similar means is NonCommercial provided there is no payment of monetary compensation in connection with the exchange.
|
| 34 |
+
|
| 35 |
+
j. __Share__ means to provide material to the public by any means or process that requires permission under the Licensed Rights, such as reproduction, public display, public performance, distribution, dissemination, communication, or importation, and to make material available to the public including in ways that members of the public may access the material from a place and at a time individually chosen by them.
|
| 36 |
+
|
| 37 |
+
k. __Sui Generis Database Rights__ means rights other than copyright resulting from Directive 96/9/EC of the European Parliament and of the Council of 11 March 1996 on the legal protection of databases, as amended and/or succeeded, as well as other essentially equivalent rights anywhere in the world.
|
| 38 |
+
|
| 39 |
+
l. __You__ means the individual or entity exercising the Licensed Rights under this Public License. Your has a corresponding meaning.
|
| 40 |
+
|
| 41 |
+
### Section 2 – Scope.
|
| 42 |
+
|
| 43 |
+
a. ___License grant.___
|
| 44 |
+
|
| 45 |
+
1. Subject to the terms and conditions of this Public License, the Licensor hereby grants You a worldwide, royalty-free, non-sublicensable, non-exclusive, irrevocable license to exercise the Licensed Rights in the Licensed Material to:
|
| 46 |
+
|
| 47 |
+
A. reproduce and Share the Licensed Material, in whole or in part, for NonCommercial purposes only; and
|
| 48 |
+
|
| 49 |
+
B. produce and reproduce, but not Share, Adapted Material for NonCommercial purposes only.
|
| 50 |
+
|
| 51 |
+
2. __Exceptions and Limitations.__ For the avoidance of doubt, where Exceptions and Limitations apply to Your use, this Public License does not apply, and You do not need to comply with its terms and conditions.
|
| 52 |
+
|
| 53 |
+
3. __Term.__ The term of this Public License is specified in Section 6(a).
|
| 54 |
+
|
| 55 |
+
4. __Media and formats; technical modifications allowed.__ The Licensor authorizes You to exercise the Licensed Rights in all media and formats whether now known or hereafter created, and to make technical modifications necessary to do so. The Licensor waives and/or agrees not to assert any right or authority to forbid You from making technical modifications necessary to exercise the Licensed Rights, including technical modifications necessary to circumvent Effective Technological Measures. For purposes of this Public License, simply making modifications authorized by this Section 2(a)(4) never produces Adapted Material.
|
| 56 |
+
|
| 57 |
+
5. __Downstream recipients.__
|
| 58 |
+
|
| 59 |
+
A. __Offer from the Licensor – Licensed Material.__ Every recipient of the Licensed Material automatically receives an offer from the Licensor to exercise the Licensed Rights under the terms and conditions of this Public License.
|
| 60 |
+
|
| 61 |
+
B. __No downstream restrictions.__ You may not offer or impose any additional or different terms or conditions on, or apply any Effective Technological Measures to, the Licensed Material if doing so restricts exercise of the Licensed Rights by any recipient of the Licensed Material.
|
| 62 |
+
|
| 63 |
+
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| 64 |
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|
| 65 |
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| 67 |
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| 68 |
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### Section 3 – License Conditions.
|
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| 75 |
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Your exercise of the Licensed Rights is expressly made subject to the following conditions.
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| 76 |
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| 80 |
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### Section 4 – Sui Generis Database Rights.
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### Section 5 – Disclaimer of Warranties and Limitation of Liability.
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c. The disclaimer of warranties and limitation of liability provided above shall be interpreted in a manner that, to the extent possible, most closely approximates an absolute disclaimer and waiver of all liability.
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### Section 6 – Term and Termination.
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|
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a. This Public License applies for the term of the Copyright and Similar Rights licensed here. However, if You fail to comply with this Public License, then Your rights under this Public License terminate automatically.
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| 131 |
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For the avoidance of doubt, this Section 6(b) does not affect any right the Licensor may have to seek remedies for Your violations of this Public License.
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d. Sections 1, 5, 6, 7, and 8 survive termination of this Public License.
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### Section 7 – Other Terms and Conditions.
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a. The Licensor shall not be bound by any additional or different terms or conditions communicated by You unless expressly agreed.
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b. Any arrangements, understandings, or agreements regarding the Licensed Material not stated herein are separate from and independent of the terms and conditions of this Public License.
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| 145 |
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### Section 8 – Interpretation.
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| 147 |
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a. For the avoidance of doubt, this Public License does not, and shall not be interpreted to, reduce, limit, restrict, or impose conditions on any use of the Licensed Material that could lawfully be made without permission under this Public License.
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b. To the extent possible, if any provision of this Public License is deemed unenforceable, it shall be automatically reformed to the minimum extent necessary to make it enforceable. If the provision cannot be reformed, it shall be severed from this Public License without affecting the enforceability of the remaining terms and conditions.
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| 150 |
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| 151 |
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c. No term or condition of this Public License will be waived and no failure to comply consented to unless expressly agreed to by the Licensor.
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> Creative Commons is not a party to its public licenses. Notwithstanding, Creative Commons may elect to apply one of its public licenses to material it publishes and in those instances will be considered the “Licensor.” Except for the limited purpose of indicating that material is shared under a Creative Commons public license or as otherwise permitted by the Creative Commons policies published at [creativecommons.org/policies](http://creativecommons.org/policies), Creative Commons does not authorize the use of the trademark “Creative Commons” or any other trademark or logo of Creative Commons without its prior written consent including, without limitation, in connection with any unauthorized modifications to any of its public licenses or any other arrangements, understandings, or agreements concerning use of licensed material. For the avoidance of doubt, this paragraph does not form part of the public licenses.
|
| 156 |
+
>
|
| 157 |
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> Creative Commons may be contacted at [creativecommons.org](http://creativecommons.org).
|
abc/README.md
ADDED
|
@@ -0,0 +1,131 @@
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|
| 1 |
+
# ChatTTS
|
| 2 |
+
[**English**](./README.md) | [**中文简体**](./README_CN.md)
|
| 3 |
+
|
| 4 |
+
ChatTTS is a text-to-speech model designed specifically for dialogue scenario such as LLM assistant. It supports both English and Chinese languages. Our model is trained with 100,000+ hours composed of chinese and english. The open-source version on HuggingFace is a 40,000 hours pre trained model without SFT.
|
| 5 |
+
|
| 6 |
+
For formal inquiries about model and roadmap, please contact us at open-source@2noise.com. You could join our QQ group: 808364215 for discussion. Adding github issues is always welcomed.
|
| 7 |
+
|
| 8 |
+
---
|
| 9 |
+
## Highlights
|
| 10 |
+
1. **Conversational TTS**: ChatTTS is optimized for dialogue-based tasks, enabling natural and expressive speech synthesis. It supports multiple speakers, facilitating interactive conversations.
|
| 11 |
+
2. **Fine-grained Control**: The model could predict and control fine-grained prosodic features, including laughter, pauses, and interjections.
|
| 12 |
+
3. **Better Prosody**: ChatTTS surpasses most of open-source TTS models in terms of prosody. We provide pretrained models to support further research and development.
|
| 13 |
+
|
| 14 |
+
For the detailed description of the model, you can refer to [video on Bilibili](https://www.bilibili.com/video/BV1zn4y1o7iV)
|
| 15 |
+
|
| 16 |
+
---
|
| 17 |
+
|
| 18 |
+
## Disclaimer
|
| 19 |
+
|
| 20 |
+
This repo is for academic purposes only. It is intended for educational and research use, and should not be used for any commercial or legal purposes. The authors do not guarantee the accuracy, completeness, or reliability of the information. The information and data used in this repo, are for academic and research purposes only. The data obtained from publicly available sources, and the authors do not claim any ownership or copyright over the data.
|
| 21 |
+
|
| 22 |
+
ChatTTS is a powerful text-to-speech system. However, it is very important to utilize this technology responsibly and ethically. To limit the use of ChatTTS, we added a small amount of high-frequency noise during the training of the 40,000-hour model, and compressed the audio quality as much as possible using MP3 format, to prevent malicious actors from potentially using it for criminal purposes. At the same time, we have internally trained a detection model and plan to open-source it in the future.
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
---
|
| 26 |
+
## Usage
|
| 27 |
+
|
| 28 |
+
<h4>basic usage</h4>
|
| 29 |
+
|
| 30 |
+
```python
|
| 31 |
+
import ChatTTS
|
| 32 |
+
from IPython.display import Audio
|
| 33 |
+
|
| 34 |
+
chat = ChatTTS.Chat()
|
| 35 |
+
chat.load_models()
|
| 36 |
+
|
| 37 |
+
texts = ["<PUT YOUR TEXT HERE>",]
|
| 38 |
+
|
| 39 |
+
wavs = chat.infer(texts, use_decoder=True)
|
| 40 |
+
Audio(wavs[0], rate=24_000, autoplay=True)
|
| 41 |
+
```
|
| 42 |
+
|
| 43 |
+
<h4>advanced usage</h4>
|
| 44 |
+
|
| 45 |
+
```python
|
| 46 |
+
###################################
|
| 47 |
+
# Sample a speaker from Gaussian.
|
| 48 |
+
import torch
|
| 49 |
+
std, mean = torch.load('ChatTTS/asset/spk_stat.pt').chunk(2)
|
| 50 |
+
rand_spk = torch.randn(768) * std + mean
|
| 51 |
+
|
| 52 |
+
params_infer_code = {
|
| 53 |
+
'spk_emb': rand_spk, # add sampled speaker
|
| 54 |
+
'temperature': .3, # using custom temperature
|
| 55 |
+
'top_P': 0.7, # top P decode
|
| 56 |
+
'top_K': 20, # top K decode
|
| 57 |
+
}
|
| 58 |
+
|
| 59 |
+
###################################
|
| 60 |
+
# For sentence level manual control.
|
| 61 |
+
|
| 62 |
+
# use oral_(0-9), laugh_(0-2), break_(0-7)
|
| 63 |
+
# to generate special token in text to synthesize.
|
| 64 |
+
params_refine_text = {
|
| 65 |
+
'prompt': '[oral_2][laugh_0][break_6]'
|
| 66 |
+
}
|
| 67 |
+
|
| 68 |
+
wav = chat.infer("<PUT YOUR TEXT HERE>", params_refine_text=params_refine_text, params_infer_code=params_infer_code)
|
| 69 |
+
|
| 70 |
+
###################################
|
| 71 |
+
# For word level manual control.
|
| 72 |
+
text = 'What is [uv_break]your favorite english food?[laugh][lbreak]'
|
| 73 |
+
wav = chat.infer(text, skip_refine_text=True, params_infer_code=params_infer_code)
|
| 74 |
+
|
| 75 |
+
```
|
| 76 |
+
|
| 77 |
+
<details open>
|
| 78 |
+
<summary><h4>Example: self introduction</h4></summary>
|
| 79 |
+
|
| 80 |
+
```python
|
| 81 |
+
inputs_en = """
|
| 82 |
+
chat T T S is a text to speech model designed for dialogue applications.
|
| 83 |
+
[uv_break]it supports mixed language input [uv_break]and offers multi speaker
|
| 84 |
+
capabilities with precise control over prosodic elements [laugh]like like
|
| 85 |
+
[uv_break]laughter[laugh], [uv_break]pauses, [uv_break]and intonation.
|
| 86 |
+
[uv_break]it delivers natural and expressive speech,[uv_break]so please
|
| 87 |
+
[uv_break] use the project responsibly at your own risk.[uv_break]
|
| 88 |
+
""".replace('\n', '') # English is still experimental.
|
| 89 |
+
|
| 90 |
+
params_refine_text = {
|
| 91 |
+
'prompt': '[oral_2][laugh_0][break_4]'
|
| 92 |
+
}
|
| 93 |
+
audio_array_cn = chat.infer(inputs_cn, params_refine_text=params_refine_text)
|
| 94 |
+
audio_array_en = chat.infer(inputs_en, params_refine_text=params_refine_text)
|
| 95 |
+
```
|
| 96 |
+
[male speaker](https://github.com/2noise/ChatTTS/assets/130631963/e0f51251-db7f-4d39-a0e9-3e095bb65de1)
|
| 97 |
+
|
| 98 |
+
[female speaker](https://github.com/2noise/ChatTTS/assets/130631963/f5dcdd01-1091-47c5-8241-c4f6aaaa8bbd)
|
| 99 |
+
</details>
|
| 100 |
+
|
| 101 |
+
---
|
| 102 |
+
## Roadmap
|
| 103 |
+
- [x] Open-source the 40k hour base model and spk_stats file
|
| 104 |
+
- [ ] Open-source VQ encoder and Lora training code
|
| 105 |
+
- [ ] Streaming audio generation without refining the text*
|
| 106 |
+
- [ ] Open-source the 40k hour version with multi-emotion control
|
| 107 |
+
- [ ] ChatTTS.cpp maybe? (PR or new repo are welcomed.)
|
| 108 |
+
|
| 109 |
+
----
|
| 110 |
+
## FAQ
|
| 111 |
+
|
| 112 |
+
##### How much VRAM do I need? How about infer speed?
|
| 113 |
+
For a 30-second audio clip, at least 4GB of GPU memory is required. For the 4090D GPU, it can generate audio corresponding to approximately 7 semantic tokens per second. The Real-Time Factor (RTF) is around 0.65.
|
| 114 |
+
|
| 115 |
+
##### model stability is not good enough, with issues such as multi speakers or poor audio quality.
|
| 116 |
+
|
| 117 |
+
This is a problem that typically occurs with autoregressive models(for bark and valle). It's generally difficult to avoid. One can try multiple samples to find a suitable result.
|
| 118 |
+
|
| 119 |
+
##### Besides laughter, can we control anything else? Can we control other emotions?
|
| 120 |
+
|
| 121 |
+
In the current released model, the only token-level control units are [laugh], [uv_break], and [lbreak]. In future versions, we may open-source models with additional emotional control capabilities.
|
| 122 |
+
|
| 123 |
+
---
|
| 124 |
+
## Acknowledgements
|
| 125 |
+
- [bark](https://github.com/suno-ai/bark), [XTTSv2](https://github.com/coqui-ai/TTS) and [valle](https://arxiv.org/abs/2301.02111) demostrate a remarkable TTS result by a autoregressive-style system.
|
| 126 |
+
- [fish-speech](https://github.com/fishaudio/fish-speech) reveals capability of GVQ as audio tokenizer for LLM modeling.
|
| 127 |
+
- [vocos](https://github.com/gemelo-ai/vocos) which is used as a pretrained vocoder.
|
| 128 |
+
|
| 129 |
+
---
|
| 130 |
+
## Special Appreciation
|
| 131 |
+
- [wlu-audio lab](https://audio.westlake.edu.cn/) for early algorithm experiments.
|
abc/README_CN.md
ADDED
|
@@ -0,0 +1,133 @@
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|
| 1 |
+
# ChatTTS
|
| 2 |
+
[**English**](./README.md) | [**中文简体**](./README_CN.md)
|
| 3 |
+
|
| 4 |
+
ChatTTS是专门为对话场景设计的文本转语音模型，例如LLM助手对话任务。它支持英文和中文两种语言。最大的模型使用了10万小时以上的中英文数据进行训练。在HuggingFace中开源的版本为4万小时训练且未SFT的版本.
|
| 5 |
+
|
| 6 |
+
如需就模型进行正式商业咨询，请发送邮件至 open-source@2noise.com。对于中文用户，您可以加入我们的QQ群：808364215 进行讨论。同时欢迎在GitHub上提出问题。如果遇到无法使用HuggingFace的情况,可以在[modelscope](https://www.modelscope.cn/models/pzc163/chatTTS)上进行下载.
|
| 7 |
+
|
| 8 |
+
---
|
| 9 |
+
## 亮点
|
| 10 |
+
1. **对话式 TTS**: ChatTTS针对对话式任务进行了优化，实现了自然流畅的语音合成，同时支持多说话人。
|
| 11 |
+
2. **细粒度控制**: 该模型能够预测和控制细粒度的韵律特征，包括笑声、停顿和插入词等。
|
| 12 |
+
3. **更好的韵律**: ChatTTS在韵律方面超越了大部分开源TTS模型。同时提供预训练模型，支持进一步的研究。
|
| 13 |
+
|
| 14 |
+
对于模型的具体介绍, 可以参考B站的[宣传视频](https://www.bilibili.com/video/BV1zn4y1o7iV)
|
| 15 |
+
|
| 16 |
+
---
|
| 17 |
+
|
| 18 |
+
## 免责声明
|
| 19 |
+
本文件中的信息仅供学术交流使用。其目的是用于教育和研究，不得用于任何商业或法律目的。作者不保证信息的准确性、完整性或可靠性。本文件中使用的信息和数据，仅用于学术研究目的。这些数据来自公开可用的来源，作者不对数据的所有权或版权提出任何主张。
|
| 20 |
+
|
| 21 |
+
ChatTTS是一个强大的文本转语音系统。然而，负责任地和符合伦理地利用这项技术是非常重要的。为了限制ChatTTS的使用，我们在4w小时模型的训练过程中添加了少量额外的高频噪音，并用mp3格式尽可能压低了音质，以防不法分子用于潜在的犯罪可能。同时我们在内部训练了检测模型，并计划在未来开放。
|
| 22 |
+
|
| 23 |
+
---
|
| 24 |
+
## 用法
|
| 25 |
+
|
| 26 |
+
<h4>基本用法</h4>
|
| 27 |
+
|
| 28 |
+
```python
|
| 29 |
+
import ChatTTS
|
| 30 |
+
from IPython.display import Audio
|
| 31 |
+
|
| 32 |
+
chat = ChatTTS.Chat()
|
| 33 |
+
chat.load_models()
|
| 34 |
+
|
| 35 |
+
texts = ["<PUT YOUR TEXT HERE>",]
|
| 36 |
+
|
| 37 |
+
wavs = chat.infer(texts, use_decoder=True)
|
| 38 |
+
Audio(wavs[0], rate=24_000, autoplay=True)
|
| 39 |
+
```
|
| 40 |
+
|
| 41 |
+
<h4>进阶用法</h4>
|
| 42 |
+
|
| 43 |
+
```python
|
| 44 |
+
###################################
|
| 45 |
+
# Sample a speaker from Gaussian.
|
| 46 |
+
import torch
|
| 47 |
+
std, mean = torch.load('ChatTTS/asset/spk_stat.pt').chunk(2)
|
| 48 |
+
rand_spk = torch.randn(768) * std + mean
|
| 49 |
+
|
| 50 |
+
params_infer_code = {
|
| 51 |
+
'spk_emb': rand_spk, # add sampled speaker
|
| 52 |
+
'temperature': .3, # using custom temperature
|
| 53 |
+
'top_P': 0.7, # top P decode
|
| 54 |
+
'top_K': 20, # top K decode
|
| 55 |
+
}
|
| 56 |
+
|
| 57 |
+
###################################
|
| 58 |
+
# For sentence level manual control.
|
| 59 |
+
|
| 60 |
+
# use oral_(0-9), laugh_(0-2), break_(0-7)
|
| 61 |
+
# to generate special token in text to synthesize.
|
| 62 |
+
params_refine_text = {
|
| 63 |
+
'prompt': '[oral_2][laugh_0][break_6]'
|
| 64 |
+
}
|
| 65 |
+
|
| 66 |
+
wav = chat.infer("<PUT YOUR TEXT HERE>", params_refine_text=params_refine_text, params_infer_code=params_infer_code)
|
| 67 |
+
|
| 68 |
+
###################################
|
| 69 |
+
# For word level manual control.
|
| 70 |
+
# use_decoder=False to infer faster with a bit worse quality
|
| 71 |
+
text = 'What is [uv_break]your favorite english food?[laugh][lbreak]'
|
| 72 |
+
wav = chat.infer(text, skip_refine_text=True, params_infer_code=params_infer_code, use_decoder=False)
|
| 73 |
+
|
| 74 |
+
```
|
| 75 |
+
|
| 76 |
+
<details open>
|
| 77 |
+
<summary><h4>自我介绍样例</h4></summary>
|
| 78 |
+
|
| 79 |
+
```python
|
| 80 |
+
inputs_cn = """
|
| 81 |
+
chat T T S 是一款强大的对话式文本转语音模型。它有中英混读和多说话人的能力。
|
| 82 |
+
chat T T S 不仅能够生成自然流畅的语音，还能控制[laugh]笑声啊[laugh]，
|
| 83 |
+
停顿啊[uv_break]语气词啊等副语言现象[uv_break]。这个韵律超越了许多开源模型[uv_break]。
|
| 84 |
+
请注意，chat T T S 的使用应遵守法律和伦理准则，避免滥用的安全风险。[uv_break]'
|
| 85 |
+
""".replace('\n', '')
|
| 86 |
+
|
| 87 |
+
params_refine_text = {
|
| 88 |
+
'prompt': '[oral_2][laugh_0][break_4]'
|
| 89 |
+
}
|
| 90 |
+
audio_array_cn = chat.infer(inputs_cn, params_refine_text=params_refine_text)
|
| 91 |
+
audio_array_en = chat.infer(inputs_en, params_refine_text=params_refine_text)
|
| 92 |
+
```
|
| 93 |
+
[男说话人](https://github.com/2noise/ChatTTS/assets/130631963/bbfa3b83-2b67-4bb6-9315-64c992b63788)
|
| 94 |
+
|
| 95 |
+
[女说话人](https://github.com/2noise/ChatTTS/assets/130631963/e061f230-0e05-45e6-8e4e-0189f2d260c4)
|
| 96 |
+
</details>
|
| 97 |
+
|
| 98 |
+
|
| 99 |
+
---
|
| 100 |
+
## 计划路线
|
| 101 |
+
- [x] 开源4w小时基础模型和spk_stats文件
|
| 102 |
+
- [ ] 开源VQ encoder和Lora 训练代码
|
| 103 |
+
- [ ] 在非refine text情况下, 流式生成音频*
|
| 104 |
+
- [ ] 开源多情感可控的4w小时版本
|
| 105 |
+
- [ ] ChatTTS.cpp maybe? (欢迎社区PR或独立的新repo)
|
| 106 |
+
|
| 107 |
+
---
|
| 108 |
+
## 常见问题
|
| 109 |
+
|
| 110 |
+
##### 连不上HuggingFace
|
| 111 |
+
请使用[modelscope](https://www.modelscope.cn/models/pzc163/chatTTS)的版本. 并设置cache的位置:
|
| 112 |
+
```python
|
| 113 |
+
|
| 114 |
+
```
|
| 115 |
+
|
| 116 |
+
##### 我要多少显存? Infer的速度是怎么样的?
|
| 117 |
+
对于30s的音频, 至少需要4G的显存. 对于4090D, 1s生成约7个字所对应的音频. RTF约0.65.
|
| 118 |
+
|
| 119 |
+
##### 模型稳定性似乎不够好, 会出现其他说话人或音质很差的现象.
|
| 120 |
+
这是自回归模型通常都会出现的问题. 说话人可能会在中间变化, 可能会采样到音质非常差的结果, 这通常难以避免. 可以多采样几次来找到合适的结果.
|
| 121 |
+
|
| 122 |
+
##### 除了笑声还能控制什么吗? 还能控制其他情感吗?
|
| 123 |
+
在现在放出的模型版本中, 只有[laugh]和[uv_break], [lbreak]作为字级别的控制单元. 在未来的版本中我们可能会开源其他情感控制的版本.
|
| 124 |
+
|
| 125 |
+
---
|
| 126 |
+
## 致谢
|
| 127 |
+
- [bark](https://github.com/suno-ai/bark),[XTTSv2](https://github.com/coqui-ai/TTS)和[valle](https://arxiv.org/abs/2301.02111)展示了自回归任务用于TTS任务的可能性.
|
| 128 |
+
- [fish-speech](https://github.com/fishaudio/fish-speech)一个优秀的自回归TTS模型, 揭示了GVQ用于LLM任务的可能性.
|
| 129 |
+
- [vocos](https://github.com/gemelo-ai/vocos)作为模型中的vocoder.
|
| 130 |
+
|
| 131 |
+
---
|
| 132 |
+
## 特别致谢
|
| 133 |
+
- [wlu-audio lab](https://audio.westlake.edu.cn/)为我们提供了早期算法试验的支持.
|
abc/infer.ipynb
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
abc/requirements.txt
ADDED
|
@@ -0,0 +1,7 @@
|
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|
| 1 |
+
omegaconf~=2.3.0
|
| 2 |
+
torch~=2.0
|
| 3 |
+
tqdm
|
| 4 |
+
einops
|
| 5 |
+
vector_quantize_pytorch
|
| 6 |
+
transformers~=4.41.1
|
| 7 |
+
vocos
|
api.py
ADDED
|
@@ -0,0 +1,361 @@
|
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|
| 1 |
+
import os
|
| 2 |
+
import sys
|
| 3 |
+
sys.path.insert(0, os.getcwd())
|
| 4 |
+
import ChatTTS
|
| 5 |
+
import re
|
| 6 |
+
import time
|
| 7 |
+
import io
|
| 8 |
+
from io import BytesIO
|
| 9 |
+
import pandas
|
| 10 |
+
import numpy as np
|
| 11 |
+
from tqdm import tqdm
|
| 12 |
+
import random
|
| 13 |
+
import os
|
| 14 |
+
import json
|
| 15 |
+
from utils import batch_split,normalize_zh
|
| 16 |
+
import torch
|
| 17 |
+
import soundfile as sf
|
| 18 |
+
import wave
|
| 19 |
+
|
| 20 |
+
from fastapi import FastAPI, Request, HTTPException, Response
|
| 21 |
+
from fastapi.responses import StreamingResponse, JSONResponse
|
| 22 |
+
|
| 23 |
+
from starlette.middleware.cors import CORSMiddleware #引入 CORS中间件模块
|
| 24 |
+
|
| 25 |
+
#设置允许访问的域名
|
| 26 |
+
origins = ["*"] #"*"，即为所有。
|
| 27 |
+
|
| 28 |
+
from pydantic import BaseModel
|
| 29 |
+
|
| 30 |
+
import uvicorn
|
| 31 |
+
|
| 32 |
+
|
| 33 |
+
from typing import Generator
|
| 34 |
+
|
| 35 |
+
|
| 36 |
+
|
| 37 |
+
chat = ChatTTS.Chat()
|
| 38 |
+
def clear_cuda_cache():
|
| 39 |
+
"""
|
| 40 |
+
Clear CUDA cache
|
| 41 |
+
:return:
|
| 42 |
+
"""
|
| 43 |
+
torch.cuda.empty_cache()
|
| 44 |
+
|
| 45 |
+
|
| 46 |
+
def deterministic(seed=0):
|
| 47 |
+
"""
|
| 48 |
+
Set random seed for reproducibility
|
| 49 |
+
:param seed:
|
| 50 |
+
:return:
|
| 51 |
+
"""
|
| 52 |
+
# ref: https://github.com/Jackiexiao/ChatTTS-api-ui-docker/blob/main/api.py#L27
|
| 53 |
+
torch.manual_seed(seed)
|
| 54 |
+
np.random.seed(seed)
|
| 55 |
+
torch.cuda.manual_seed(seed)
|
| 56 |
+
torch.backends.cudnn.deterministic = True
|
| 57 |
+
torch.backends.cudnn.benchmark = False
|
| 58 |
+
|
| 59 |
+
|
| 60 |
+
class TTS_Request(BaseModel):
|
| 61 |
+
text: str = None
|
| 62 |
+
seed: int = 2581
|
| 63 |
+
speed: int = 3
|
| 64 |
+
media_type: str = "wav"
|
| 65 |
+
streaming: int = 0
|
| 66 |
+
|
| 67 |
+
|
| 68 |
+
|
| 69 |
+
|
| 70 |
+
|
| 71 |
+
|
| 72 |
+
app = FastAPI()
|
| 73 |
+
|
| 74 |
+
app.add_middleware(
|
| 75 |
+
CORSMiddleware,
|
| 76 |
+
allow_origins=origins, #设置允许的origins来源
|
| 77 |
+
allow_credentials=True,
|
| 78 |
+
allow_methods=["*"], # 设置允许跨域的http方法，比如 get、post、put等。
|
| 79 |
+
allow_headers=["*"]) #允许跨域的headers，可以用来鉴别来源等作用。
|
| 80 |
+
|
| 81 |
+
|
| 82 |
+
def cut5(inp):
|
| 83 |
+
# if not re.search(r'[^\w\s]', inp[-1]):
|
| 84 |
+
# inp += '。'
|
| 85 |
+
inp = inp.strip("\n")
|
| 86 |
+
punds = r'[,.;?!、，。？！;：…]'
|
| 87 |
+
items = re.split(f'({punds})', inp)
|
| 88 |
+
mergeitems = ["".join(group) for group in zip(items[::2], items[1::2])]
|
| 89 |
+
# 在句子不存在符号或句尾无符号的时候保证文本完整
|
| 90 |
+
if len(items)%2 == 1:
|
| 91 |
+
mergeitems.append(items[-1])
|
| 92 |
+
# opt = "\n".join(mergeitems)
|
| 93 |
+
return mergeitems
|
| 94 |
+
|
| 95 |
+
# from https://huggingface.co/spaces/coqui/voice-chat-with-mistral/blob/main/app.py
|
| 96 |
+
def wave_header_chunk(frame_input=b"", channels=1, sample_width=2, sample_rate=24000):
|
| 97 |
+
# This will create a wave header then append the frame input
|
| 98 |
+
# It should be first on a streaming wav file
|
| 99 |
+
# Other frames better should not have it (else you will hear some artifacts each chunk start)
|
| 100 |
+
wav_buf = BytesIO()
|
| 101 |
+
with wave.open(wav_buf, "wb") as vfout:
|
| 102 |
+
vfout.setnchannels(channels)
|
| 103 |
+
vfout.setsampwidth(sample_width)
|
| 104 |
+
vfout.setframerate(sample_rate)
|
| 105 |
+
vfout.writeframes(frame_input)
|
| 106 |
+
|
| 107 |
+
wav_buf.seek(0)
|
| 108 |
+
return wav_buf.read()
|
| 109 |
+
|
| 110 |
+
|
| 111 |
+
|
| 112 |
+
### modify from https://github.com/RVC-Boss/GPT-SoVITS/pull/894/files
|
| 113 |
+
def pack_ogg(io_buffer:BytesIO, data:np.ndarray, rate:int):
|
| 114 |
+
|
| 115 |
+
with sf.SoundFile(io_buffer, mode='w',samplerate=rate, channels=1, format='ogg') as audio_file:
|
| 116 |
+
audio_file.write(data)
|
| 117 |
+
return io_buffer
|
| 118 |
+
|
| 119 |
+
|
| 120 |
+
def pack_raw(io_buffer:BytesIO, data:np.ndarray, rate:int):
|
| 121 |
+
io_buffer.write(data.tobytes())
|
| 122 |
+
return io_buffer
|
| 123 |
+
|
| 124 |
+
|
| 125 |
+
def pack_wav(io_buffer:BytesIO, data:np.ndarray, rate:int):
|
| 126 |
+
io_buffer = BytesIO()
|
| 127 |
+
sf.write(io_buffer, data, rate, format='wav')
|
| 128 |
+
return io_buffer
|
| 129 |
+
|
| 130 |
+
|
| 131 |
+
def pack_aac(io_buffer:BytesIO, data:np.ndarray, rate:int):
|
| 132 |
+
process = subprocess.Popen([
|
| 133 |
+
'ffmpeg',
|
| 134 |
+
'-f', 's16le', # 输入16位有符号小端整数PCM
|
| 135 |
+
'-ar', str(rate), # 设置采样率
|
| 136 |
+
'-ac', '1', # 单声道
|
| 137 |
+
'-i', 'pipe:0', # 从管道读取输入
|
| 138 |
+
'-c:a', 'aac', # 音频编码器为AAC
|
| 139 |
+
'-b:a', '192k', # 比特率
|
| 140 |
+
'-vn', # 不包含视频
|
| 141 |
+
'-f', 'adts', # 输出AAC数据流格式
|
| 142 |
+
'pipe:1' # 将输出写入管道
|
| 143 |
+
], stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
|
| 144 |
+
out, _ = process.communicate(input=data.tobytes())
|
| 145 |
+
io_buffer.write(out)
|
| 146 |
+
return io_buffer
|
| 147 |
+
|
| 148 |
+
def pack_audio(io_buffer:BytesIO, data:np.ndarray, rate:int, media_type:str):
|
| 149 |
+
|
| 150 |
+
if media_type == "ogg":
|
| 151 |
+
io_buffer = pack_ogg(io_buffer, data, rate)
|
| 152 |
+
elif media_type == "aac":
|
| 153 |
+
io_buffer = pack_aac(io_buffer, data, rate)
|
| 154 |
+
elif media_type == "wav":
|
| 155 |
+
io_buffer = pack_wav(io_buffer, data, rate)
|
| 156 |
+
else:
|
| 157 |
+
io_buffer = pack_raw(io_buffer, data, rate)
|
| 158 |
+
io_buffer.seek(0)
|
| 159 |
+
return io_buffer
|
| 160 |
+
|
| 161 |
+
|
| 162 |
+
def generate_tts_audio(text_file,seed=2581,speed=1, oral=0, laugh=0, bk=4, min_length=80, batch_size=5, temperature=0.01, top_P=0.7,
|
| 163 |
+
top_K=20,streaming=0,cur_tqdm=None):
|
| 164 |
+
|
| 165 |
+
from utils import combine_audio, save_audio, batch_split
|
| 166 |
+
|
| 167 |
+
from utils import split_text, replace_tokens, restore_tokens
|
| 168 |
+
|
| 169 |
+
|
| 170 |
+
if seed in [0, -1, None]:
|
| 171 |
+
seed = random.randint(1, 9999)
|
| 172 |
+
|
| 173 |
+
|
| 174 |
+
content = text_file
|
| 175 |
+
# texts = split_text(content, min_length=min_length)
|
| 176 |
+
|
| 177 |
+
|
| 178 |
+
# if oral < 0 or oral > 9 or laugh < 0 or laugh > 2 or bk < 0 or bk > 7:
|
| 179 |
+
# raise ValueError("oral_(0-9), laugh_(0-2), break_(0-7) out of range")
|
| 180 |
+
|
| 181 |
+
# refine_text_prompt = f"[oral_{oral}][laugh_{laugh}][break_{bk}]"
|
| 182 |
+
|
| 183 |
+
# 将 [uv_break] [laugh] 替换为 _uv_break_ _laugh_ 处理后再还原
|
| 184 |
+
content = replace_tokens(content)
|
| 185 |
+
texts = split_text(content, min_length=min_length)
|
| 186 |
+
for i, text in enumerate(texts):
|
| 187 |
+
texts[i] = restore_tokens(text)
|
| 188 |
+
|
| 189 |
+
if oral < 0 or oral > 9 or laugh < 0 or laugh > 2 or bk < 0 or bk > 7:
|
| 190 |
+
raise ValueError("oral_(0-9), laugh_(0-2), break_(0-7) out of range")
|
| 191 |
+
|
| 192 |
+
refine_text_prompt = f"[oral_{oral}][laugh_{laugh}][break_{bk}]"
|
| 193 |
+
|
| 194 |
+
|
| 195 |
+
deterministic(seed)
|
| 196 |
+
rnd_spk_emb = chat.sample_random_speaker()
|
| 197 |
+
params_infer_code = {
|
| 198 |
+
'spk_emb': rnd_spk_emb,
|
| 199 |
+
'prompt': f'[speed_{speed}]',
|
| 200 |
+
'top_P': top_P,
|
| 201 |
+
'top_K': top_K,
|
| 202 |
+
'temperature': temperature
|
| 203 |
+
}
|
| 204 |
+
params_refine_text = {
|
| 205 |
+
'prompt': refine_text_prompt,
|
| 206 |
+
'top_P': top_P,
|
| 207 |
+
'top_K': top_K,
|
| 208 |
+
'temperature': temperature
|
| 209 |
+
}
|
| 210 |
+
|
| 211 |
+
|
| 212 |
+
|
| 213 |
+
if not cur_tqdm:
|
| 214 |
+
cur_tqdm = tqdm
|
| 215 |
+
|
| 216 |
+
start_time = time.time()
|
| 217 |
+
|
| 218 |
+
if not streaming:
|
| 219 |
+
|
| 220 |
+
all_wavs = []
|
| 221 |
+
|
| 222 |
+
|
| 223 |
+
for batch in cur_tqdm(batch_split(texts, batch_size), desc=f"Inferring audio for seed={seed}"):
|
| 224 |
+
|
| 225 |
+
print(batch)
|
| 226 |
+
wavs = chat.infer(batch, params_infer_code=params_infer_code, params_refine_text=params_refine_text,use_decoder=True, skip_refine_text=True)
|
| 227 |
+
audio_data = wavs[0][0]
|
| 228 |
+
audio_data = audio_data / np.max(np.abs(audio_data))
|
| 229 |
+
|
| 230 |
+
|
| 231 |
+
all_wavs.append(audio_data)
|
| 232 |
+
|
| 233 |
+
# all_wavs.extend(wavs)
|
| 234 |
+
|
| 235 |
+
clear_cuda_cache()
|
| 236 |
+
|
| 237 |
+
|
| 238 |
+
|
| 239 |
+
audio = (np.concatenate(all_wavs) * 32768).astype(
|
| 240 |
+
np.int16
|
| 241 |
+
)
|
| 242 |
+
|
| 243 |
+
# end_time = time.time()
|
| 244 |
+
# elapsed_time = end_time - start_time
|
| 245 |
+
# print(f"Saving audio for seed {seed}, took {elapsed_time:.2f}s")
|
| 246 |
+
|
| 247 |
+
yield audio
|
| 248 |
+
|
| 249 |
+
|
| 250 |
+
else:
|
| 251 |
+
|
| 252 |
+
print("流式生成")
|
| 253 |
+
|
| 254 |
+
texts = [normalize_zh(_) for _ in content.split('\n') if _.strip()]
|
| 255 |
+
|
| 256 |
+
|
| 257 |
+
for text in texts:
|
| 258 |
+
|
| 259 |
+
wavs_gen = chat.infer(text, params_infer_code=params_infer_code, params_refine_text=params_refine_text,use_decoder=True, skip_refine_text=True,stream=True)
|
| 260 |
+
|
| 261 |
+
for gen in wavs_gen:
|
| 262 |
+
wavs = [np.array([[]])]
|
| 263 |
+
wavs[0] = np.hstack([wavs[0], np.array(gen[0])])
|
| 264 |
+
audio_data = wavs[0][0]
|
| 265 |
+
|
| 266 |
+
audio_data = audio_data / np.max(np.abs(audio_data))
|
| 267 |
+
|
| 268 |
+
|
| 269 |
+
|
| 270 |
+
yield (audio_data * 32767).astype(np.int16)
|
| 271 |
+
|
| 272 |
+
# clear_cuda_cache()
|
| 273 |
+
|
| 274 |
+
|
| 275 |
+
|
| 276 |
+
|
| 277 |
+
|
| 278 |
+
async def tts_handle(req:dict):
|
| 279 |
+
|
| 280 |
+
media_type = req["media_type"]
|
| 281 |
+
|
| 282 |
+
print(req["streaming"])
|
| 283 |
+
print(req["media_type"])
|
| 284 |
+
|
| 285 |
+
if not req["streaming"]:
|
| 286 |
+
|
| 287 |
+
audio_data = next(generate_tts_audio(req["text"],req["seed"]))
|
| 288 |
+
|
| 289 |
+
# print(audio_data)
|
| 290 |
+
|
| 291 |
+
sr = 24000
|
| 292 |
+
|
| 293 |
+
audio_data = pack_audio(BytesIO(), audio_data, sr, media_type).getvalue()
|
| 294 |
+
|
| 295 |
+
|
| 296 |
+
return Response(audio_data, media_type=f"audio/{media_type}")
|
| 297 |
+
|
| 298 |
+
|
| 299 |
+
# return FileResponse(f"./{audio_data}", media_type="audio/wav")
|
| 300 |
+
|
| 301 |
+
else:
|
| 302 |
+
|
| 303 |
+
tts_generator = generate_tts_audio(req["text"],req["seed"],streaming=1)
|
| 304 |
+
|
| 305 |
+
sr = 24000
|
| 306 |
+
|
| 307 |
+
def streaming_generator(tts_generator:Generator, media_type:str):
|
| 308 |
+
if media_type == "wav":
|
| 309 |
+
yield wave_header_chunk()
|
| 310 |
+
media_type = "raw"
|
| 311 |
+
for chunk in tts_generator:
|
| 312 |
+
print(chunk)
|
| 313 |
+
yield pack_audio(BytesIO(), chunk, sr, media_type).getvalue()
|
| 314 |
+
|
| 315 |
+
return StreamingResponse(streaming_generator(tts_generator, media_type), media_type=f"audio/{media_type}")
|
| 316 |
+
|
| 317 |
+
|
| 318 |
+
|
| 319 |
+
@app.get("/")
|
| 320 |
+
async def tts_get(text: str = None,media_type:str = "wav",seed:int = 2581,streaming:int = 0):
|
| 321 |
+
req = {
|
| 322 |
+
"text": text,
|
| 323 |
+
"media_type": media_type,
|
| 324 |
+
"seed": seed,
|
| 325 |
+
"streaming": streaming,
|
| 326 |
+
}
|
| 327 |
+
return await tts_handle(req)
|
| 328 |
+
|
| 329 |
+
|
| 330 |
+
@app.get("/speakers")
|
| 331 |
+
def speakers_endpoint():
|
| 332 |
+
return JSONResponse([{"name":"default","vid":1}], status_code=200)
|
| 333 |
+
|
| 334 |
+
|
| 335 |
+
@app.get("/speakers_list")
|
| 336 |
+
def speakerlist_endpoint():
|
| 337 |
+
return JSONResponse(["female_calm","female","male"], status_code=200)
|
| 338 |
+
|
| 339 |
+
|
| 340 |
+
@app.post("/")
|
| 341 |
+
async def tts_post_endpoint(request: TTS_Request):
|
| 342 |
+
req = request.dict()
|
| 343 |
+
return await tts_handle(req)
|
| 344 |
+
|
| 345 |
+
|
| 346 |
+
@app.post("/tts_to_audio/")
|
| 347 |
+
async def tts_to_audio(request: TTS_Request):
|
| 348 |
+
req = request.dict()
|
| 349 |
+
from config import llama_seed
|
| 350 |
+
|
| 351 |
+
req["seed"] = llama_seed
|
| 352 |
+
|
| 353 |
+
return await tts_handle(req)
|
| 354 |
+
|
| 355 |
+
if __name__ == "__main__":
|
| 356 |
+
|
| 357 |
+
chat.load_models(source="local", local_path="models")
|
| 358 |
+
|
| 359 |
+
# chat = load_chat_tts_model(source="local", local_path="models")
|
| 360 |
+
|
| 361 |
+
uvicorn.run(app,host='0.0.0.0',port=9880,workers=1)
|
assets/shot1.png
ADDED
|
assets/shot2.png
ADDED
|
assets/shot3.png
ADDED
|
chattts_webui_mix.ipynb
ADDED
|
@@ -0,0 +1,65 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"nbformat": 4,
|
| 3 |
+
"nbformat_minor": 0,
|
| 4 |
+
"metadata": {
|
| 5 |
+
"colab": {
|
| 6 |
+
"provenance": [],
|
| 7 |
+
"gpuType": "T4"
|
| 8 |
+
},
|
| 9 |
+
"kernelspec": {
|
| 10 |
+
"name": "python3",
|
| 11 |
+
"display_name": "Python 3"
|
| 12 |
+
},
|
| 13 |
+
"language_info": {
|
| 14 |
+
"name": "python"
|
| 15 |
+
},
|
| 16 |
+
"accelerator": "GPU"
|
| 17 |
+
},
|
| 18 |
+
"cells": [
|
| 19 |
+
{
|
| 20 |
+
"cell_type": "markdown",
|
| 21 |
+
"source": [
|
| 22 |
+
"> 🌟 如果你觉得 ChatTTS 和 ChatTTS_colab 项目对你有帮助，请访问以下链接给它们点个星星吧！🌟\n",
|
| 23 |
+
"\n",
|
| 24 |
+
"- [ChatTTS 项目](https://github.com/2noise/ChatTTS)\n",
|
| 25 |
+
"\n",
|
| 26 |
+
"- [ChatTTS_colab 项目](https://github.com/6drf21e/ChatTTS_colab)\n",
|
| 27 |
+
"\n",
|
| 28 |
+
"感谢你的支持！\n",
|
| 29 |
+
"\n",
|
| 30 |
+
"# 运行方法\n",
|
| 31 |
+
"\n",
|
| 32 |
+
"- 点击菜单栏的--代码执行程序--全部运行即可\n",
|
| 33 |
+
"- 执行后在下方的日志中找到类似\n",
|
| 34 |
+
"\n",
|
| 35 |
+
" Running on public URL: https://**************.gradio.live <-这个就是可以访问的公网地址\n",
|
| 36 |
+
"\n",
|
| 37 |
+
"安装包的时候提示要重启 请点**\"否\"**"
|
| 38 |
+
],
|
| 39 |
+
"metadata": {
|
| 40 |
+
"id": "Xo3k5XsTzWK6"
|
| 41 |
+
}
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"cell_type": "code",
|
| 45 |
+
"source": [
|
| 46 |
+
"!git clone -q https://github.com/6drf21e/ChatTTS_colab\n",
|
| 47 |
+
"%cd ChatTTS_colab\n",
|
| 48 |
+
"!git clone -q https://github.com/2noise/ChatTTS\n",
|
| 49 |
+
"%cd ChatTTS\n",
|
| 50 |
+
"!git checkout -q e6412b1\n",
|
| 51 |
+
"%cd ..\n",
|
| 52 |
+
"!mv ChatTTS abc\n",
|
| 53 |
+
"!mv abc/* /content/ChatTTS_colab/\n",
|
| 54 |
+
"!pip install -q omegaconf vocos vector_quantize_pytorch gradio cn2an pypinyin openai jieba WeTextProcessing python-dotenv\n",
|
| 55 |
+
"# 启动 Gradio 有公网地址\n",
|
| 56 |
+
"!python webui_mix.py --share\n"
|
| 57 |
+
],
|
| 58 |
+
"metadata": {
|
| 59 |
+
"id": "hNDl-5muR77-"
|
| 60 |
+
},
|
| 61 |
+
"execution_count": null,
|
| 62 |
+
"outputs": []
|
| 63 |
+
}
|
| 64 |
+
]
|
| 65 |
+
}
|
cli.py
ADDED
|
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import argparse
|
| 2 |
+
import os
|
| 3 |
+
from tts_model import load_chat_tts_model, tts
|
| 4 |
+
from config import DEFAULT_SPEED, DEFAULT_ORAL, DEFAULT_LAUGH, DEFAULT_BK, DEFAULT_SEG_LENGTH, DEFAULT_BATCH_SIZE
|
| 5 |
+
|
| 6 |
+
if __name__ == "__main__":
|
| 7 |
+
parser = argparse.ArgumentParser(description="Generate TTS audio from text file.")
|
| 8 |
+
parser.add_argument("--text_file", type=str, required=True, help="Path to the text file to convert.")
|
| 9 |
+
parser.add_argument("--seed", type=int,
|
| 10 |
+
help="Specific seed for generating audio. If not provided, seeds will be random.")
|
| 11 |
+
parser.add_argument("--speed", type=int, default=DEFAULT_SPEED, help="Speed of generated audio.")
|
| 12 |
+
parser.add_argument("--oral", type=int, default=DEFAULT_ORAL, help="Oral")
|
| 13 |
+
parser.add_argument("--laugh", type=int, default=DEFAULT_LAUGH, help="Laugh")
|
| 14 |
+
parser.add_argument("--bk", type=int, default=DEFAULT_BK, help="Break")
|
| 15 |
+
parser.add_argument("--seg", type=int, default=DEFAULT_SEG_LENGTH, help="Max len of text segments.")
|
| 16 |
+
parser.add_argument("--batch", type=int, default=DEFAULT_BATCH_SIZE, help="Batch size for TTS inference.")
|
| 17 |
+
parser.add_argument("--source", type=str, default="huggingface", help="Model source: 'huggingface' or 'local'.")
|
| 18 |
+
parser.add_argument("--local_path", type=str, help="Path to local model if source is 'local'.")
|
| 19 |
+
|
| 20 |
+
args = parser.parse_args()
|
| 21 |
+
chat = load_chat_tts_model(source=args.source, local_path=args.local_path)
|
| 22 |
+
# chat = None
|
| 23 |
+
tts(chat, args.text_file, args.seed, args.speed, args.oral, args.laugh, args.bk, args.seg,
|
| 24 |
+
args.batch)
|
config.py
ADDED
|
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Description: Configuration file for the project
|
| 2 |
+
llama_seed = 2581
|
| 3 |
+
DEFAULT_DIR = "output"
|
| 4 |
+
DEFAULT_SPEED = 5
|
| 5 |
+
DEFAULT_ORAL = 2
|
| 6 |
+
DEFAULT_LAUGH = 0
|
| 7 |
+
DEFAULT_BK = 4
|
| 8 |
+
# 段落切割
|
| 9 |
+
DEFAULT_SEG_LENGTH = 80
|
| 10 |
+
DEFAULT_BATCH_SIZE = 3
|
| 11 |
+
# 温度
|
| 12 |
+
DEFAULT_TEMPERATURE = 0.1
|
| 13 |
+
# top_P
|
| 14 |
+
DEFAULT_TOP_P = 0.7
|
| 15 |
+
# top_K
|
| 16 |
+
DEFAULT_TOP_K = 20
|
| 17 |
+
# LLM settings
|
| 18 |
+
LLM_RETRIES = 1
|
| 19 |
+
LLM_REQUEST_INTERVAL = 0.5
|
| 20 |
+
LLM_RETRY_DELAY = 1.1
|
| 21 |
+
LLM_MAX_TEXT_LENGTH = 2000
|
| 22 |
+
LLM_PROMPT = """
|
| 23 |
+
角色: 你是一位专业的剧本编辑，擅长将故事文本转化为适合舞台或屏幕的剧本格式。
|
| 24 |
+
技能: 剧本编辑、角色分析、文本转换、JSON格式处理。
|
| 25 |
+
目标: 你需要将一个故事转换成旁白和各个角色的文本，并且希望最终的输出格式是JSON。
|
| 26 |
+
限制条件: 确保转换的文本保留故事的原意，并且角色对话清晰、易于理解。
|
| 27 |
+
输出格式: JSON格式(python可解析)，包含旁白和各个角色的对话。
|
| 28 |
+
工作流程:
|
| 29 |
+
- 阅读并理解原始故事文本。
|
| 30 |
+
- 将故事文本分解为大段的旁白和丰富角色对话。旁白应确保听众能够理解故事，包含细节、引人入胜。角色分配的 character 要符合角色身份。
|
| 31 |
+
- 将旁白和角色对话格式化为JSON。
|
| 32 |
+
示例:
|
| 33 |
+
故事文本: "在一个遥远的王国里，有一位勇敢的骑士和一位美丽的公主。有一天骑士遇到了公主。骑士说道：公主你真漂亮！。“谢谢你 亲爱的骑士先生”"
|
| 34 |
+
转换后的JSON格式:
|
| 35 |
+
```
|
| 36 |
+
[
|
| 37 |
+
{"txt": "在一个遥远的王国里，有一位勇敢的骑士和一位美丽的公主。有一天骑士遇到了公主。", "character": "旁白"},
|
| 38 |
+
{"txt": "骑士说道", "character": "旁白"},
|
| 39 |
+
{"txt": "公主你真漂亮！", "character": "年轻男性"},
|
| 40 |
+
{"txt": "谢谢你 亲爱的骑士先生", "character": "年轻女性"}
|
| 41 |
+
]
|
| 42 |
+
```
|
| 43 |
+
注意: character 字段的值需要使用类似 "旁白"、"年轻男性"、"年轻女性" 等角色身份。如果有多个角色，可以使用 "年轻男性1"、"年轻男性2" 等。
|
| 44 |
+
|
| 45 |
+
--故事文本--
|
| 46 |
+
"""
|
llm_utils.py
ADDED
|
@@ -0,0 +1,119 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
try:
|
| 2 |
+
import openai
|
| 3 |
+
except ImportError:
|
| 4 |
+
print("The 'openai' module is not installed. Please install it using 'pip install openai'.")
|
| 5 |
+
exit(1)
|
| 6 |
+
import json
|
| 7 |
+
import re
|
| 8 |
+
import time
|
| 9 |
+
from tqdm import tqdm
|
| 10 |
+
from config import LLM_RETRIES, LLM_REQUEST_INTERVAL, LLM_RETRY_DELAY, LLM_MAX_TEXT_LENGTH, LLM_PROMPT
|
| 11 |
+
|
| 12 |
+
|
| 13 |
+
def send_request(client, prompt, text, model):
|
| 14 |
+
text = remove_json_escape_characters(text)
|
| 15 |
+
messages = [{"role": "user", "content": f"{prompt}\n\n{text}"}]
|
| 16 |
+
try:
|
| 17 |
+
response = client.chat.completions.create(model=model, messages=messages, max_tokens=4096)
|
| 18 |
+
print(response)
|
| 19 |
+
return response.choices[0].message.content
|
| 20 |
+
except openai.OpenAIError as e:
|
| 21 |
+
print(f"OpenAI API error: {e}")
|
| 22 |
+
return None
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
def clean_text(text):
|
| 26 |
+
import re
|
| 27 |
+
if isinstance(text, str):
|
| 28 |
+
# 移除 ASCII 控制字符（0-31 和 127）
|
| 29 |
+
text = re.sub(r'[\x00-\x1F\x7F]', '', text)
|
| 30 |
+
return text
|
| 31 |
+
|
| 32 |
+
|
| 33 |
+
def extract_json(response_text):
|
| 34 |
+
with open("debug.txt", "w", encoding="utf8") as f:
|
| 35 |
+
f.write(response_text)
|
| 36 |
+
pattern = re.compile(r'((\[[^\}]{3,})?\{s*[^\}\{]{3,}?:.*\}([^\{]+\])?)', re.M | re.S)
|
| 37 |
+
match = re.search(pattern, response_text)
|
| 38 |
+
if match:
|
| 39 |
+
return match.group(0)
|
| 40 |
+
return None
|
| 41 |
+
|
| 42 |
+
|
| 43 |
+
def clean_and_load_json(json_string):
|
| 44 |
+
try:
|
| 45 |
+
cleaned_json_string = json_string.replace("'", '"')
|
| 46 |
+
cleaned_json_string = clean_text(cleaned_json_string)
|
| 47 |
+
# debug 写入文本
|
| 48 |
+
with open("debug.json", "w", encoding="utf8") as f:
|
| 49 |
+
f.write(cleaned_json_string)
|
| 50 |
+
json_obj = json.loads(cleaned_json_string)
|
| 51 |
+
return json_obj
|
| 52 |
+
except json.JSONDecodeError as e:
|
| 53 |
+
print(f"JSON decode error: {e}")
|
| 54 |
+
return None
|
| 55 |
+
|
| 56 |
+
|
| 57 |
+
def validate_json(json_obj, required_keys):
|
| 58 |
+
return isinstance(json_obj, list)
|
| 59 |
+
print(json_obj)
|
| 60 |
+
return True
|
| 61 |
+
if json_obj and all(key in json_obj for key in required_keys):
|
| 62 |
+
return True
|
| 63 |
+
return False
|
| 64 |
+
|
| 65 |
+
|
| 66 |
+
def process_text(client, prompt, text, model, required_keys):
|
| 67 |
+
parts = [text[i:i + LLM_MAX_TEXT_LENGTH] for i in range(0, len(text), LLM_MAX_TEXT_LENGTH)]
|
| 68 |
+
results = []
|
| 69 |
+
|
| 70 |
+
for part in tqdm(parts, desc="Processing text"):
|
| 71 |
+
for attempt in range(LLM_RETRIES + 1):
|
| 72 |
+
response = send_request(client, prompt, part, model)
|
| 73 |
+
if response:
|
| 74 |
+
json_string = extract_json(response)
|
| 75 |
+
if json_string:
|
| 76 |
+
json_obj = clean_and_load_json(json_string)
|
| 77 |
+
if validate_json(json_obj, required_keys):
|
| 78 |
+
results.extend(json_obj)
|
| 79 |
+
break
|
| 80 |
+
else:
|
| 81 |
+
print(f"Invalid JSON structure. Retrying ({attempt + 1}/{LLM_RETRIES})...")
|
| 82 |
+
else:
|
| 83 |
+
print(f"No JSON found in response. Retrying ({attempt + 1}/{LLM_RETRIES})...")
|
| 84 |
+
else:
|
| 85 |
+
print(f"API request failed. Retrying ({attempt + 1}/{LLM_RETRIES})...")
|
| 86 |
+
time.sleep(LLM_RETRY_DELAY)
|
| 87 |
+
time.sleep(LLM_REQUEST_INTERVAL)
|
| 88 |
+
|
| 89 |
+
return results
|
| 90 |
+
|
| 91 |
+
|
| 92 |
+
def llm_operation(api_base, api_key, model, prompt, text, required_keys):
|
| 93 |
+
client = openai.OpenAI(api_key=api_key, base_url=api_base)
|
| 94 |
+
return process_text(client, prompt, text, model, required_keys)
|
| 95 |
+
|
| 96 |
+
|
| 97 |
+
def remove_json_escape_characters(s):
|
| 98 |
+
"""
|
| 99 |
+
移除用户提交文本中容易被llm输出导致json校验出错的字符
|
| 100 |
+
:param s:
|
| 101 |
+
:return:
|
| 102 |
+
"""
|
| 103 |
+
# 定义需要移除的字符
|
| 104 |
+
escape_chars = {
|
| 105 |
+
'"': '',
|
| 106 |
+
'\\': '',
|
| 107 |
+
'/': '',
|
| 108 |
+
'\b': '',
|
| 109 |
+
'\f': '',
|
| 110 |
+
'\n': '',
|
| 111 |
+
'\r': '',
|
| 112 |
+
'\t': '',
|
| 113 |
+
}
|
| 114 |
+
escape_re = re.compile('|'.join(re.escape(key) for key in escape_chars.keys()))
|
| 115 |
+
|
| 116 |
+
def replace(match):
|
| 117 |
+
return escape_chars[match.group(0)]
|
| 118 |
+
|
| 119 |
+
return escape_re.sub(replace, s)
|
requirements-macos.txt
ADDED
|
@@ -0,0 +1,97 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
aiofiles
|
| 2 |
+
altair
|
| 3 |
+
annotated-types
|
| 4 |
+
antlr4-python3-runtime
|
| 5 |
+
anyio
|
| 6 |
+
attrs
|
| 7 |
+
certifi
|
| 8 |
+
charset-normalizer
|
| 9 |
+
click
|
| 10 |
+
cn2an
|
| 11 |
+
contourpy
|
| 12 |
+
cycler
|
| 13 |
+
distro
|
| 14 |
+
dnspython
|
| 15 |
+
einops
|
| 16 |
+
einx
|
| 17 |
+
email_validator
|
| 18 |
+
encodec
|
| 19 |
+
fastapi
|
| 20 |
+
fastapi-cli
|
| 21 |
+
ffmpy
|
| 22 |
+
filelock
|
| 23 |
+
fonttools
|
| 24 |
+
frozendict
|
| 25 |
+
fsspec
|
| 26 |
+
gradio
|
| 27 |
+
gradio_client
|
| 28 |
+
h11
|
| 29 |
+
httpcore
|
| 30 |
+
httptools
|
| 31 |
+
httpx
|
| 32 |
+
huggingface-hub
|
| 33 |
+
idna
|
| 34 |
+
importlib_resources
|
| 35 |
+
jieba
|
| 36 |
+
Jinja2
|
| 37 |
+
jsonschema
|
| 38 |
+
jsonschema-specifications
|
| 39 |
+
kiwisolver
|
| 40 |
+
markdown-it-py
|
| 41 |
+
MarkupSafe
|
| 42 |
+
matplotlib
|
| 43 |
+
mdurl
|
| 44 |
+
mpmath
|
| 45 |
+
networkx
|
| 46 |
+
numpy
|
| 47 |
+
omegaconf
|
| 48 |
+
openai
|
| 49 |
+
orjson
|
| 50 |
+
packaging
|
| 51 |
+
pandas
|
| 52 |
+
pillow
|
| 53 |
+
proces
|
| 54 |
+
pydantic
|
| 55 |
+
pydantic_core
|
| 56 |
+
pydub
|
| 57 |
+
Pygments
|
| 58 |
+
pyparsing
|
| 59 |
+
pypinyin
|
| 60 |
+
python-dateutil
|
| 61 |
+
python-dotenv
|
| 62 |
+
python-multipart
|
| 63 |
+
pytz
|
| 64 |
+
PyYAML
|
| 65 |
+
referencing
|
| 66 |
+
regex
|
| 67 |
+
requests
|
| 68 |
+
rich
|
| 69 |
+
rpds-py
|
| 70 |
+
ruff
|
| 71 |
+
safetensors
|
| 72 |
+
scipy
|
| 73 |
+
semantic-version
|
| 74 |
+
shellingham
|
| 75 |
+
six
|
| 76 |
+
sniffio
|
| 77 |
+
socksio
|
| 78 |
+
starlette
|
| 79 |
+
sympy
|
| 80 |
+
tokenizers
|
| 81 |
+
tomlkit
|
| 82 |
+
toolz
|
| 83 |
+
torch
|
| 84 |
+
torchaudio
|
| 85 |
+
tqdm
|
| 86 |
+
transformers
|
| 87 |
+
typer
|
| 88 |
+
typing_extensions
|
| 89 |
+
tzdata
|
| 90 |
+
ujson
|
| 91 |
+
urllib3
|
| 92 |
+
uvicorn
|
| 93 |
+
uvloop
|
| 94 |
+
vector-quantize-pytorch
|
| 95 |
+
vocos
|
| 96 |
+
watchfiles
|
| 97 |
+
websockets
|
requirements.txt
ADDED
|
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
cn2an
|
| 2 |
+
pypinyin
|
| 3 |
+
openai
|
| 4 |
+
WeTextProcessing
|
slct_voice_240605.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tts_model.py
ADDED
|
@@ -0,0 +1,175 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import datetime
|
| 2 |
+
import json
|
| 3 |
+
import os
|
| 4 |
+
import re
|
| 5 |
+
import time
|
| 6 |
+
|
| 7 |
+
import numpy as np
|
| 8 |
+
import torch
|
| 9 |
+
from tqdm import tqdm
|
| 10 |
+
|
| 11 |
+
import ChatTTS
|
| 12 |
+
from config import DEFAULT_TEMPERATURE, DEFAULT_TOP_P, DEFAULT_TOP_K
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
def load_chat_tts_model(source='huggingface', force_redownload=False, local_path=None):
|
| 16 |
+
"""
|
| 17 |
+
Load ChatTTS model
|
| 18 |
+
:param source:
|
| 19 |
+
:param force_redownload:
|
| 20 |
+
:param local_path:
|
| 21 |
+
:return:
|
| 22 |
+
"""
|
| 23 |
+
print("Loading ChatTTS model...")
|
| 24 |
+
chat = ChatTTS.Chat()
|
| 25 |
+
chat.load_models(source=source, force_redownload=force_redownload, custom_path=local_path, compile=False)
|
| 26 |
+
return chat
|
| 27 |
+
|
| 28 |
+
|
| 29 |
+
def clear_cuda_cache():
|
| 30 |
+
"""
|
| 31 |
+
Clear CUDA cache
|
| 32 |
+
:return:
|
| 33 |
+
"""
|
| 34 |
+
torch.cuda.empty_cache()
|
| 35 |
+
|
| 36 |
+
|
| 37 |
+
def deterministic(seed=0):
|
| 38 |
+
"""
|
| 39 |
+
Set random seed for reproducibility
|
| 40 |
+
:param seed:
|
| 41 |
+
:return:
|
| 42 |
+
"""
|
| 43 |
+
# ref: https://github.com/Jackiexiao/ChatTTS-api-ui-docker/blob/main/api.py#L27
|
| 44 |
+
torch.manual_seed(seed)
|
| 45 |
+
np.random.seed(seed)
|
| 46 |
+
torch.cuda.manual_seed(seed)
|
| 47 |
+
torch.backends.cudnn.deterministic = True
|
| 48 |
+
torch.backends.cudnn.benchmark = False
|
| 49 |
+
|
| 50 |
+
|
| 51 |
+
def generate_audio_for_seed(chat, seed, texts, batch_size, speed, refine_text_prompt, roleid=None,
|
| 52 |
+
temperature=DEFAULT_TEMPERATURE,
|
| 53 |
+
top_P=DEFAULT_TOP_P, top_K=DEFAULT_TOP_K, cur_tqdm=None, skip_save=False,
|
| 54 |
+
skip_refine_text=False, speaker_type="seed", pt_file=None):
|
| 55 |
+
from utils import combine_audio, save_audio, batch_split
|
| 56 |
+
print(f"speaker_type: {speaker_type}")
|
| 57 |
+
if speaker_type == "seed":
|
| 58 |
+
if seed in [None, -1, 0, "", "random"]:
|
| 59 |
+
seed = np.random.randint(0, 9999)
|
| 60 |
+
deterministic(seed)
|
| 61 |
+
rnd_spk_emb = chat.sample_random_speaker()
|
| 62 |
+
elif speaker_type == "role":
|
| 63 |
+
# 从 JSON 文件中读取数据
|
| 64 |
+
with open('./slct_voice_240605.json', 'r', encoding='utf-8') as json_file:
|
| 65 |
+
slct_idx_loaded = json.load(json_file)
|
| 66 |
+
# 将包含 Tensor 数据的部分转换回 Tensor 对象
|
| 67 |
+
for key in slct_idx_loaded:
|
| 68 |
+
tensor_list = slct_idx_loaded[key]["tensor"]
|
| 69 |
+
slct_idx_loaded[key]["tensor"] = torch.tensor(tensor_list)
|
| 70 |
+
# 将音色 tensor 打包进params_infer_code，固定使用此音色发音，调低temperature
|
| 71 |
+
rnd_spk_emb = slct_idx_loaded[roleid]["tensor"]
|
| 72 |
+
# temperature = 0.001
|
| 73 |
+
elif speaker_type == "pt":
|
| 74 |
+
print(pt_file)
|
| 75 |
+
rnd_spk_emb = torch.load(pt_file)
|
| 76 |
+
print(rnd_spk_emb.shape)
|
| 77 |
+
if rnd_spk_emb.shape != (768,):
|
| 78 |
+
raise ValueError("维度应为 768。")
|
| 79 |
+
else:
|
| 80 |
+
raise ValueError(f"Invalid speaker_type: {speaker_type}. ")
|
| 81 |
+
|
| 82 |
+
params_infer_code = {
|
| 83 |
+
'spk_emb': rnd_spk_emb,
|
| 84 |
+
'prompt': f'[speed_{speed}]',
|
| 85 |
+
'top_P': top_P,
|
| 86 |
+
'top_K': top_K,
|
| 87 |
+
'temperature': temperature
|
| 88 |
+
}
|
| 89 |
+
params_refine_text = {
|
| 90 |
+
'prompt': refine_text_prompt,
|
| 91 |
+
'top_P': top_P,
|
| 92 |
+
'top_K': top_K,
|
| 93 |
+
'temperature': temperature
|
| 94 |
+
}
|
| 95 |
+
all_wavs = []
|
| 96 |
+
start_time = time.time()
|
| 97 |
+
total = len(texts)
|
| 98 |
+
flag = 0
|
| 99 |
+
if not cur_tqdm:
|
| 100 |
+
cur_tqdm = tqdm
|
| 101 |
+
|
| 102 |
+
if re.search(r'\[uv_break\]|\[laugh\]', ''.join(texts)) is not None:
|
| 103 |
+
if not skip_refine_text:
|
| 104 |
+
print("Detected [uv_break] or [laugh] in text, skipping refine_text")
|
| 105 |
+
skip_refine_text = True
|
| 106 |
+
|
| 107 |
+
for batch in cur_tqdm(batch_split(texts, batch_size), desc=f"Inferring audio for seed={seed}"):
|
| 108 |
+
flag += len(batch)
|
| 109 |
+
_params_infer_code = {**params_infer_code}
|
| 110 |
+
wavs = chat.infer(batch, params_infer_code=_params_infer_code, params_refine_text=params_refine_text,
|
| 111 |
+
use_decoder=True, skip_refine_text=skip_refine_text)
|
| 112 |
+
all_wavs.extend(wavs)
|
| 113 |
+
clear_cuda_cache()
|
| 114 |
+
if skip_save:
|
| 115 |
+
return all_wavs
|
| 116 |
+
combined_audio = combine_audio(all_wavs)
|
| 117 |
+
end_time = time.time()
|
| 118 |
+
elapsed_time = end_time - start_time
|
| 119 |
+
print(f"Saving audio for seed {seed}, took {elapsed_time:.2f}s")
|
| 120 |
+
timestamp = datetime.datetime.now().strftime('%Y-%m-%d_%H%M%S')
|
| 121 |
+
wav_filename = f"chattts-[seed_{seed}][speed_{speed}]{refine_text_prompt}[{timestamp}].wav"
|
| 122 |
+
return save_audio(wav_filename, combined_audio)
|
| 123 |
+
|
| 124 |
+
|
| 125 |
+
def generate_refine_text(chat, seed, text, refine_text_prompt, temperature=DEFAULT_TEMPERATURE,
|
| 126 |
+
top_P=DEFAULT_TOP_P, top_K=DEFAULT_TOP_K):
|
| 127 |
+
if seed in [None, -1, 0, "", "random"]:
|
| 128 |
+
seed = np.random.randint(0, 9999)
|
| 129 |
+
|
| 130 |
+
deterministic(seed)
|
| 131 |
+
|
| 132 |
+
params_refine_text = {
|
| 133 |
+
'prompt': refine_text_prompt,
|
| 134 |
+
'top_P': top_P,
|
| 135 |
+
'top_K': top_K,
|
| 136 |
+
'temperature': temperature
|
| 137 |
+
}
|
| 138 |
+
print('params_refine_text:', text)
|
| 139 |
+
print('refine_text_prompt:', refine_text_prompt)
|
| 140 |
+
refine_text = chat.infer(text, params_refine_text=params_refine_text, refine_text_only=True, skip_refine_text=False)
|
| 141 |
+
print('refine_text:', refine_text)
|
| 142 |
+
return refine_text
|
| 143 |
+
|
| 144 |
+
|
| 145 |
+
def tts(chat, text_file, seed, speed, oral, laugh, bk, seg, batch, progres=None):
|
| 146 |
+
"""
|
| 147 |
+
Text-to-Speech
|
| 148 |
+
:param chat: ChatTTS model
|
| 149 |
+
:param text_file: Text file or string
|
| 150 |
+
:param seed: Seed
|
| 151 |
+
:param speed: Speed
|
| 152 |
+
:param oral: Oral
|
| 153 |
+
:param laugh: Laugh
|
| 154 |
+
:param bk:
|
| 155 |
+
:param seg:
|
| 156 |
+
:param batch:
|
| 157 |
+
:param progres:
|
| 158 |
+
:return:
|
| 159 |
+
"""
|
| 160 |
+
from utils import read_long_text, split_text
|
| 161 |
+
|
| 162 |
+
if os.path.isfile(text_file):
|
| 163 |
+
content = read_long_text(text_file)
|
| 164 |
+
elif isinstance(text_file, str):
|
| 165 |
+
content = text_file
|
| 166 |
+
texts = split_text(content, min_length=seg)
|
| 167 |
+
|
| 168 |
+
print(texts)
|
| 169 |
+
# exit()
|
| 170 |
+
|
| 171 |
+
if oral < 0 or oral > 9 or laugh < 0 or laugh > 2 or bk < 0 or bk > 7:
|
| 172 |
+
raise ValueError("oral_(0-9), laugh_(0-2), break_(0-7) out of range")
|
| 173 |
+
|
| 174 |
+
refine_text_prompt = f"[oral_{oral}][laugh_{laugh}][break_{bk}]"
|
| 175 |
+
return generate_audio_for_seed(chat, seed, texts, batch, speed, refine_text_prompt)
|
utils.py
ADDED
|
@@ -0,0 +1,333 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
| 1 |
+
try:
|
| 2 |
+
import cn2an
|
| 3 |
+
except ImportError:
|
| 4 |
+
print("The 'cn2an' module is not installed. Please install it using 'pip install cn2an'.")
|
| 5 |
+
exit(1)
|
| 6 |
+
|
| 7 |
+
try:
|
| 8 |
+
import jieba
|
| 9 |
+
except ImportError:
|
| 10 |
+
print("The 'jieba' module is not installed. Please install it using 'pip install jieba'.")
|
| 11 |
+
exit(1)
|
| 12 |
+
|
| 13 |
+
import re
|
| 14 |
+
import numpy as np
|
| 15 |
+
import wave
|
| 16 |
+
import jieba.posseg as pseg
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
def save_audio(file_name, audio, rate=24000):
|
| 20 |
+
"""
|
| 21 |
+
保存音频文件
|
| 22 |
+
:param file_name:
|
| 23 |
+
:param audio:
|
| 24 |
+
:param rate:
|
| 25 |
+
:return:
|
| 26 |
+
"""
|
| 27 |
+
import os
|
| 28 |
+
from config import DEFAULT_DIR
|
| 29 |
+
audio = (audio * 32767).astype(np.int16)
|
| 30 |
+
|
| 31 |
+
# 检查默认目录
|
| 32 |
+
if not os.path.exists(DEFAULT_DIR):
|
| 33 |
+
os.makedirs(DEFAULT_DIR)
|
| 34 |
+
full_path = os.path.join(DEFAULT_DIR, file_name)
|
| 35 |
+
with wave.open(full_path, "w") as wf:
|
| 36 |
+
wf.setnchannels(1)
|
| 37 |
+
wf.setsampwidth(2)
|
| 38 |
+
wf.setframerate(rate)
|
| 39 |
+
wf.writeframes(audio.tobytes())
|
| 40 |
+
return full_path
|
| 41 |
+
|
| 42 |
+
|
| 43 |
+
def combine_audio(wavs):
|
| 44 |
+
"""
|
| 45 |
+
合并多段音频
|
| 46 |
+
:param wavs:
|
| 47 |
+
:return:
|
| 48 |
+
"""
|
| 49 |
+
wavs = [normalize_audio(w) for w in wavs] # 先对每段音频归一化
|
| 50 |
+
combined_audio = np.concatenate(wavs, axis=1) # 沿着时间轴合并
|
| 51 |
+
return normalize_audio(combined_audio) # 合并后再次归一化
|
| 52 |
+
|
| 53 |
+
|
| 54 |
+
def normalize_audio(audio):
|
| 55 |
+
"""
|
| 56 |
+
Normalize audio array to be between -1 and 1
|
| 57 |
+
:param audio: Input audio array
|
| 58 |
+
:return: Normalized audio array
|
| 59 |
+
"""
|
| 60 |
+
audio = np.clip(audio, -1, 1)
|
| 61 |
+
max_val = np.max(np.abs(audio))
|
| 62 |
+
if max_val > 0:
|
| 63 |
+
audio = audio / max_val
|
| 64 |
+
return audio
|
| 65 |
+
|
| 66 |
+
|
| 67 |
+
def combine_audio_with_crossfade(audio_arrays, crossfade_duration=0.1, rate=24000):
|
| 68 |
+
"""
|
| 69 |
+
Combine audio arrays with crossfade to avoid clipping noise at the junctions.
|
| 70 |
+
:param audio_arrays: List of audio arrays to combine
|
| 71 |
+
:param crossfade_duration: Duration of the crossfade in seconds
|
| 72 |
+
:param rate: Sample rate of the audio
|
| 73 |
+
:return: Combined audio array
|
| 74 |
+
"""
|
| 75 |
+
crossfade_samples = int(crossfade_duration * rate)
|
| 76 |
+
combined_audio = np.array([], dtype=np.float32)
|
| 77 |
+
|
| 78 |
+
for i in range(len(audio_arrays)):
|
| 79 |
+
audio_arrays[i] = np.squeeze(audio_arrays[i]) # Ensure all arrays are 1D
|
| 80 |
+
if i == 0:
|
| 81 |
+
combined_audio = audio_arrays[i] # Start with the first audio array
|
| 82 |
+
else:
|
| 83 |
+
# Apply crossfade between the end of the current combined audio and the start of the next array
|
| 84 |
+
overlap = np.minimum(len(combined_audio), crossfade_samples)
|
| 85 |
+
crossfade_end = combined_audio[-overlap:]
|
| 86 |
+
crossfade_start = audio_arrays[i][:overlap]
|
| 87 |
+
# Crossfade by linearly blending the audio samples
|
| 88 |
+
t = np.linspace(0, 1, overlap)
|
| 89 |
+
crossfaded = crossfade_end * (1 - t) + crossfade_start * t
|
| 90 |
+
# Combine audio by replacing the end of the current combined audio with the crossfaded audio
|
| 91 |
+
combined_audio[-overlap:] = crossfaded
|
| 92 |
+
# Append the rest of the new array
|
| 93 |
+
combined_audio = np.concatenate((combined_audio, audio_arrays[i][overlap:]))
|
| 94 |
+
|
| 95 |
+
return combined_audio
|
| 96 |
+
|
| 97 |
+
|
| 98 |
+
def remove_chinese_punctuation(text):
|
| 99 |
+
"""
|
| 100 |
+
移除文本中的中文标点符号 [：；！（），【】『』「」《》－‘“’”:,;!\(\)\[\]><\-] 替换为 ，
|
| 101 |
+
:param text:
|
| 102 |
+
:return:
|
| 103 |
+
"""
|
| 104 |
+
chinese_punctuation_pattern = r"[：；！（），【】『』「」《》－‘“’”:,;!\(\)\[\]><\-·]"
|
| 105 |
+
text = re.sub(chinese_punctuation_pattern, '，', text)
|
| 106 |
+
# 使用正则表达式将多个连续的句号替换为一个句号
|
| 107 |
+
text = re.sub(r'[。，]{2,}', '。', text)
|
| 108 |
+
# 删除开头和结尾的 ， 号
|
| 109 |
+
text = re.sub(r'^，|，$', '', text)
|
| 110 |
+
return text
|
| 111 |
+
|
| 112 |
+
def remove_english_punctuation(text):
|
| 113 |
+
"""
|
| 114 |
+
移除文本中的中文标点符号 [：；！（），【】『』「」《》－‘“’”:,;!\(\)\[\]><\-] 替换为 ，
|
| 115 |
+
:param text:
|
| 116 |
+
:return:
|
| 117 |
+
"""
|
| 118 |
+
chinese_punctuation_pattern = r"[：；！（），【】『』「」《》－‘“’”:,;!\(\)\[\]><\-·]"
|
| 119 |
+
text = re.sub(chinese_punctuation_pattern, ',', text)
|
| 120 |
+
# 使用正则表达式将多个连续的句号替换为一个句号
|
| 121 |
+
text = re.sub(r'[,\.]{2,}', '.', text)
|
| 122 |
+
# 删除开头和结尾的 ， 号
|
| 123 |
+
text = re.sub(r'^,|,$', '', text)
|
| 124 |
+
return text
|
| 125 |
+
|
| 126 |
+
|
| 127 |
+
def text_normalize(text):
|
| 128 |
+
"""
|
| 129 |
+
对文本进行归一化处理 （PaddlePaddle版本）
|
| 130 |
+
:param text:
|
| 131 |
+
:return:
|
| 132 |
+
"""
|
| 133 |
+
from zh_normalization import TextNormalizer
|
| 134 |
+
# ref: https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/paddlespeech/t2s/frontend/zh_normalization
|
| 135 |
+
tx = TextNormalizer()
|
| 136 |
+
sentences = tx.normalize(text)
|
| 137 |
+
_txt = ''.join(sentences)
|
| 138 |
+
return _txt
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
def convert_numbers_to_chinese(text):
|
| 142 |
+
"""
|
| 143 |
+
将文本中的数字转换为中文数字 例如 123 -> 一百二十三
|
| 144 |
+
:param text:
|
| 145 |
+
:return:
|
| 146 |
+
"""
|
| 147 |
+
return cn2an.transform(text, "an2cn")
|
| 148 |
+
|
| 149 |
+
|
| 150 |
+
def detect_language(sentence):
|
| 151 |
+
# ref: https://github.com/2noise/ChatTTS/blob/main/ChatTTS/utils/infer_utils.py#L55
|
| 152 |
+
chinese_char_pattern = re.compile(r'[\u4e00-\u9fff]')
|
| 153 |
+
english_word_pattern = re.compile(r'\b[A-Za-z]+\b')
|
| 154 |
+
|
| 155 |
+
chinese_chars = chinese_char_pattern.findall(sentence)
|
| 156 |
+
english_words = english_word_pattern.findall(sentence)
|
| 157 |
+
|
| 158 |
+
if len(chinese_chars) > len(english_words):
|
| 159 |
+
return "zh"
|
| 160 |
+
else:
|
| 161 |
+
return "en"
|
| 162 |
+
|
| 163 |
+
|
| 164 |
+
def split_text(text, min_length=60):
|
| 165 |
+
"""
|
| 166 |
+
将文本分割为长度不小于min_length的句子
|
| 167 |
+
:param text:
|
| 168 |
+
:param min_length:
|
| 169 |
+
:return:
|
| 170 |
+
"""
|
| 171 |
+
# 短句分割符号
|
| 172 |
+
sentence_delimiters = re.compile(r'([。？！\.]+)')
|
| 173 |
+
# 匹配多个连续的回车符 作为段落点 强制分段
|
| 174 |
+
paragraph_delimiters = re.compile(r'(\s*\n\s*)+')
|
| 175 |
+
|
| 176 |
+
paragraphs = re.split(paragraph_delimiters, text)
|
| 177 |
+
|
| 178 |
+
result = []
|
| 179 |
+
|
| 180 |
+
for paragraph in paragraphs:
|
| 181 |
+
if not paragraph.strip():
|
| 182 |
+
continue # 跳过空段落
|
| 183 |
+
# 小于阈值的段落直接分开
|
| 184 |
+
if len(paragraph.strip()) < min_length:
|
| 185 |
+
result.append(paragraph.strip())
|
| 186 |
+
continue
|
| 187 |
+
# 大于的再计算拆分
|
| 188 |
+
sentences = re.split(sentence_delimiters, paragraph)
|
| 189 |
+
current_sentence = ''
|
| 190 |
+
for sentence in sentences:
|
| 191 |
+
if re.match(sentence_delimiters, sentence):
|
| 192 |
+
current_sentence += sentence.strip() + ''
|
| 193 |
+
if len(current_sentence) >= min_length:
|
| 194 |
+
result.append(current_sentence.strip())
|
| 195 |
+
current_sentence = ''
|
| 196 |
+
else:
|
| 197 |
+
current_sentence += sentence.strip()
|
| 198 |
+
|
| 199 |
+
if current_sentence:
|
| 200 |
+
if len(current_sentence) < min_length and len(result) > 0:
|
| 201 |
+
result[-1] += current_sentence
|
| 202 |
+
else:
|
| 203 |
+
result.append(current_sentence)
|
| 204 |
+
if detect_language(text[:1024]) == "zh":
|
| 205 |
+
result = [normalize_zh(_.strip()) for _ in result if _.strip()]
|
| 206 |
+
else:
|
| 207 |
+
result = [normalize_en(_.strip()) for _ in result if _.strip()]
|
| 208 |
+
return result
|
| 209 |
+
|
| 210 |
+
|
| 211 |
+
def normalize_en(text):
|
| 212 |
+
# 不再在 ChatTTS 外正则化文本
|
| 213 |
+
# from tn.english.normalizer import Normalizer
|
| 214 |
+
# normalizer = Normalizer()
|
| 215 |
+
# text = normalizer.normalize(text)
|
| 216 |
+
# text = remove_english_punctuation(text)
|
| 217 |
+
return text
|
| 218 |
+
|
| 219 |
+
|
| 220 |
+
def normalize_zh(text):
|
| 221 |
+
# 不再在 ChatTTS 外正则化文本
|
| 222 |
+
# from tn.chinese.normalizer import Normalizer
|
| 223 |
+
# normalizer = Normalizer()
|
| 224 |
+
# text = normalizer.normalize(text)
|
| 225 |
+
# text = remove_chinese_punctuation(text)
|
| 226 |
+
text = process_ddd(text)
|
| 227 |
+
return text
|
| 228 |
+
|
| 229 |
+
|
| 230 |
+
def batch_split(items, batch_size=5):
|
| 231 |
+
"""
|
| 232 |
+
将items划分为大小为batch_size的批次
|
| 233 |
+
:param items:
|
| 234 |
+
:param batch_size:
|
| 235 |
+
:return:
|
| 236 |
+
"""
|
| 237 |
+
return [items[i:i + batch_size] for i in range(0, len(items), batch_size)]
|
| 238 |
+
|
| 239 |
+
|
| 240 |
+
# 读取 txt 文件，支持自动判断文件编码
|
| 241 |
+
def read_long_text(file_path):
|
| 242 |
+
"""
|
| 243 |
+
读取长文本文件，自动判断文件编码
|
| 244 |
+
:param file_path: 文件路径
|
| 245 |
+
:return: 文本内容
|
| 246 |
+
"""
|
| 247 |
+
encodings = ['utf-8', 'gbk', 'iso-8859-1', 'utf-16']
|
| 248 |
+
|
| 249 |
+
for encoding in encodings:
|
| 250 |
+
try:
|
| 251 |
+
with open(file_path, 'r', encoding=encoding) as file:
|
| 252 |
+
return file.read()
|
| 253 |
+
except (UnicodeDecodeError, LookupError):
|
| 254 |
+
continue
|
| 255 |
+
|
| 256 |
+
raise ValueError("无法识别文件编码")
|
| 257 |
+
|
| 258 |
+
|
| 259 |
+
def replace_tokens(text):
|
| 260 |
+
remove_tokens = ['UNK']
|
| 261 |
+
for token in remove_tokens:
|
| 262 |
+
text = re.sub(r'\[' + re.escape(token) + r'\]', '', text)
|
| 263 |
+
|
| 264 |
+
tokens = ['uv_break', 'laugh','lbreak']
|
| 265 |
+
for token in tokens:
|
| 266 |
+
text = re.sub(r'\[' + re.escape(token) + r'\]', f'uu{token}uu', text)
|
| 267 |
+
text = text.replace('_', '')
|
| 268 |
+
return text
|
| 269 |
+
|
| 270 |
+
|
| 271 |
+
def restore_tokens(text):
|
| 272 |
+
tokens = ['uvbreak', 'laugh', 'UNK', 'lbreak']
|
| 273 |
+
for token in tokens:
|
| 274 |
+
text = re.sub(r'uu' + re.escape(token) + r'uu', f'[{token}]', text)
|
| 275 |
+
text = text.replace('[uvbreak]', '[uv_break]')
|
| 276 |
+
return text
|
| 277 |
+
|
| 278 |
+
|
| 279 |
+
def process_ddd(text):
|
| 280 |
+
"""
|
| 281 |
+
处理“地”、“得” 字的使用，都替换为“的”
|
| 282 |
+
依据：地、得的使用，主要是在动词和形容词前后，本方法没有严格按照语法替换，因为时常遇到用错的情况。
|
| 283 |
+
另外受 jieba 分词准确率的影响，部分情况下可能会出漏掉。例如：小红帽疑惑地问
|
| 284 |
+
:param text: 输入的文本
|
| 285 |
+
:return: 处理后的文本
|
| 286 |
+
"""
|
| 287 |
+
word_list = [(word, flag) for word, flag in pseg.cut(text, use_paddle=False)]
|
| 288 |
+
# print(word_list)
|
| 289 |
+
processed_words = []
|
| 290 |
+
for i, (word, flag) in enumerate(word_list):
|
| 291 |
+
if word in ["地", "得"]:
|
| 292 |
+
# Check previous and next word's flag
|
| 293 |
+
# prev_flag = word_list[i - 1][1] if i > 0 else None
|
| 294 |
+
# next_flag = word_list[i + 1][1] if i + 1 < len(word_list) else None
|
| 295 |
+
|
| 296 |
+
# if prev_flag in ['v', 'a'] or next_flag in ['v', 'a']:
|
| 297 |
+
if flag in ['uv', 'ud']:
|
| 298 |
+
processed_words.append("的")
|
| 299 |
+
else:
|
| 300 |
+
processed_words.append(word)
|
| 301 |
+
else:
|
| 302 |
+
processed_words.append(word)
|
| 303 |
+
|
| 304 |
+
return ''.join(processed_words)
|
| 305 |
+
|
| 306 |
+
|
| 307 |
+
def replace_space_between_chinese(text):
|
| 308 |
+
return re.sub(r'(?<=[\u4e00-\u9fff])\s+(?=[\u4e00-\u9fff])', '', text)
|
| 309 |
+
|
| 310 |
+
|
| 311 |
+
if __name__ == '__main__':
|
| 312 |
+
# txts = [
|
| 313 |
+
# "快速地跑过红色的大门",
|
| 314 |
+
# "笑得很开心，学得很好",
|
| 315 |
+
# "小红帽疑惑地问？",
|
| 316 |
+
# "大灰狼慌张地回答",
|
| 317 |
+
# "哦，这是为了更好地听你说话。",
|
| 318 |
+
# "大灰狼不耐烦地说：“为了更好地抱你。”",
|
| 319 |
+
# "他跑得很快，工作做得非常认真，这是他努力地结果。得到",
|
| 320 |
+
# ]
|
| 321 |
+
# for txt in txts:
|
| 322 |
+
# print(txt, '-->', process_ddd(txt))
|
| 323 |
+
|
| 324 |
+
txts = [
|
| 325 |
+
"电影中梁朝伟扮演的陈永仁的编号27149",
|
| 326 |
+
"这块黄金重达324.75克 我们班的最高总分为583分",
|
| 327 |
+
"12\~23 -1.5\~2",
|
| 328 |
+
"居维埃·拉色别德①、杜梅里②、卡特法日③，"
|
| 329 |
+
|
| 330 |
+
]
|
| 331 |
+
for txt in txts:
|
| 332 |
+
print(txt, '-->', text_normalize(txt))
|
| 333 |
+
# print(txt, '-->', convert_numbers_to_chinese(txt))
|
webui_mix.py
ADDED
|
@@ -0,0 +1,1036 @@
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|
| 1 |
+
import os
|
| 2 |
+
import sys
|
| 3 |
+
|
| 4 |
+
sys.path.insert(0, os.getcwd())
|
| 5 |
+
import argparse
|
| 6 |
+
import re
|
| 7 |
+
import time
|
| 8 |
+
|
| 9 |
+
import pandas
|
| 10 |
+
import numpy as np
|
| 11 |
+
from tqdm import tqdm
|
| 12 |
+
import random
|
| 13 |
+
import gradio as gr
|
| 14 |
+
import json
|
| 15 |
+
from utils import normalize_zh, batch_split, normalize_audio, combine_audio
|
| 16 |
+
from tts_model import load_chat_tts_model, clear_cuda_cache, generate_audio_for_seed
|
| 17 |
+
from config import DEFAULT_BATCH_SIZE, DEFAULT_SPEED, DEFAULT_TEMPERATURE, DEFAULT_TOP_K, DEFAULT_TOP_P, DEFAULT_ORAL, \
|
| 18 |
+
DEFAULT_LAUGH, DEFAULT_BK, DEFAULT_SEG_LENGTH
|
| 19 |
+
import torch
|
| 20 |
+
|
| 21 |
+
parser = argparse.ArgumentParser(description="Gradio ChatTTS MIX")
|
| 22 |
+
parser.add_argument("--source", type=str, default="huggingface", help="Model source: 'huggingface' or 'local'.")
|
| 23 |
+
parser.add_argument("--local_path", type=str, help="Path to local model if source is 'local'.")
|
| 24 |
+
parser.add_argument("--share", default=False, action="store_true", help="Share the server publicly.")
|
| 25 |
+
|
| 26 |
+
args = parser.parse_args()
|
| 27 |
+
|
| 28 |
+
# 存放音频种子文件的目录
|
| 29 |
+
SAVED_DIR = "saved_seeds"
|
| 30 |
+
|
| 31 |
+
# mkdir
|
| 32 |
+
if not os.path.exists(SAVED_DIR):
|
| 33 |
+
os.makedirs(SAVED_DIR)
|
| 34 |
+
|
| 35 |
+
# 文件路径
|
| 36 |
+
SAVED_SEEDS_FILE = os.path.join(SAVED_DIR, "saved_seeds.json")
|
| 37 |
+
|
| 38 |
+
# 选中的种子index
|
| 39 |
+
SELECTED_SEED_INDEX = -1
|
| 40 |
+
|
| 41 |
+
# 初始化JSON文件
|
| 42 |
+
if not os.path.exists(SAVED_SEEDS_FILE):
|
| 43 |
+
with open(SAVED_SEEDS_FILE, "w") as f:
|
| 44 |
+
f.write("[]")
|
| 45 |
+
|
| 46 |
+
chat = load_chat_tts_model(source=args.source, local_path=args.local_path)
|
| 47 |
+
# chat = None
|
| 48 |
+
# chat = load_chat_tts_model(source="local", local_path=r"models")
|
| 49 |
+
|
| 50 |
+
# 抽卡的最大数量
|
| 51 |
+
max_audio_components = 10
|
| 52 |
+
|
| 53 |
+
# 加载
|
| 54 |
+
def load_seeds():
|
| 55 |
+
with open(SAVED_SEEDS_FILE, "r") as f:
|
| 56 |
+
global saved_seeds
|
| 57 |
+
|
| 58 |
+
seeds = json.load(f)
|
| 59 |
+
|
| 60 |
+
# 兼容旧的 JSON 格式，添加 path 字段
|
| 61 |
+
for seed in seeds:
|
| 62 |
+
if 'path' not in seed:
|
| 63 |
+
seed['path'] = None
|
| 64 |
+
|
| 65 |
+
saved_seeds = seeds
|
| 66 |
+
return saved_seeds
|
| 67 |
+
|
| 68 |
+
|
| 69 |
+
def display_seeds():
|
| 70 |
+
seeds = load_seeds()
|
| 71 |
+
# 转换为 List[List] 的形式
|
| 72 |
+
return [[i, s['seed'], s['name'], s['path']] for i, s in enumerate(seeds)]
|
| 73 |
+
|
| 74 |
+
|
| 75 |
+
saved_seeds = load_seeds()
|
| 76 |
+
num_seeds_default = 2
|
| 77 |
+
|
| 78 |
+
|
| 79 |
+
def save_seeds():
|
| 80 |
+
global saved_seeds
|
| 81 |
+
with open(SAVED_SEEDS_FILE, "w") as f:
|
| 82 |
+
json.dump(saved_seeds, f)
|
| 83 |
+
saved_seeds = load_seeds()
|
| 84 |
+
|
| 85 |
+
|
| 86 |
+
# 添加 seed
|
| 87 |
+
def add_seed(seed, name, audio_path, save=True):
|
| 88 |
+
for s in saved_seeds:
|
| 89 |
+
if s['seed'] == seed:
|
| 90 |
+
return False
|
| 91 |
+
saved_seeds.append({
|
| 92 |
+
'seed': seed,
|
| 93 |
+
'name': name,
|
| 94 |
+
'path': audio_path
|
| 95 |
+
})
|
| 96 |
+
if save:
|
| 97 |
+
save_seeds()
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
# 修改 seed
|
| 101 |
+
def modify_seed(seed, name, save=True):
|
| 102 |
+
for s in saved_seeds:
|
| 103 |
+
if s['seed'] == seed:
|
| 104 |
+
s['name'] = name
|
| 105 |
+
if save:
|
| 106 |
+
save_seeds()
|
| 107 |
+
return True
|
| 108 |
+
return False
|
| 109 |
+
|
| 110 |
+
|
| 111 |
+
def delete_seed(seed, save=True):
|
| 112 |
+
for s in saved_seeds:
|
| 113 |
+
if s['seed'] == seed:
|
| 114 |
+
saved_seeds.remove(s)
|
| 115 |
+
if save:
|
| 116 |
+
save_seeds()
|
| 117 |
+
return True
|
| 118 |
+
return False
|
| 119 |
+
|
| 120 |
+
|
| 121 |
+
def generate_seeds(num_seeds, texts, tq):
|
| 122 |
+
"""
|
| 123 |
+
生成随机音频种子并保存
|
| 124 |
+
:param num_seeds:
|
| 125 |
+
:param texts:
|
| 126 |
+
:param tq:
|
| 127 |
+
:return:
|
| 128 |
+
"""
|
| 129 |
+
seeds = []
|
| 130 |
+
sample_rate = 24000
|
| 131 |
+
# 按行分割文本 并正则化数字和标点字符
|
| 132 |
+
texts = [normalize_zh(_) for _ in texts.split('\n') if _.strip()]
|
| 133 |
+
print(texts)
|
| 134 |
+
if not tq:
|
| 135 |
+
tq = tqdm
|
| 136 |
+
for _ in tq(range(num_seeds), desc=f"随机音色生成中..."):
|
| 137 |
+
seed = np.random.randint(0, 9999)
|
| 138 |
+
|
| 139 |
+
filename = generate_audio_for_seed(chat, seed, texts, 1, 5, "[oral_2][laugh_0][break_4]", None, 0.3, 0.7, 20)
|
| 140 |
+
seeds.append((filename, seed))
|
| 141 |
+
clear_cuda_cache()
|
| 142 |
+
|
| 143 |
+
return seeds
|
| 144 |
+
|
| 145 |
+
|
| 146 |
+
# 保存选定的音频种子
|
| 147 |
+
def do_save_seed(seed, audio_path):
|
| 148 |
+
print(f"Saving seed {seed} to {audio_path}")
|
| 149 |
+
seed = seed.replace('保存种子 ', '').strip()
|
| 150 |
+
if not seed:
|
| 151 |
+
return
|
| 152 |
+
add_seed(int(seed), seed, audio_path)
|
| 153 |
+
gr.Info(f"Seed {seed} has been saved.")
|
| 154 |
+
|
| 155 |
+
|
| 156 |
+
def do_save_seeds(seeds):
|
| 157 |
+
assert isinstance(seeds, pandas.DataFrame)
|
| 158 |
+
|
| 159 |
+
seeds = seeds.drop(columns=['Index'])
|
| 160 |
+
|
| 161 |
+
# 将 DataFrame 转换为字典列表格式，并将键转换为小写
|
| 162 |
+
result = [{k.lower(): v for k, v in row.items()} for row in seeds.to_dict(orient='records')]
|
| 163 |
+
print(result)
|
| 164 |
+
if result:
|
| 165 |
+
global saved_seeds
|
| 166 |
+
saved_seeds = result
|
| 167 |
+
save_seeds()
|
| 168 |
+
gr.Info(f"Seeds have been saved.")
|
| 169 |
+
return result
|
| 170 |
+
|
| 171 |
+
|
| 172 |
+
def do_delete_seed(val):
|
| 173 |
+
# 从 val 匹配 [(\d+)] 获取index
|
| 174 |
+
index = re.search(r'\[(\d+)\]', val)
|
| 175 |
+
global saved_seeds
|
| 176 |
+
if index:
|
| 177 |
+
index = int(index.group(1))
|
| 178 |
+
seed = saved_seeds[index]['seed']
|
| 179 |
+
delete_seed(seed)
|
| 180 |
+
gr.Info(f"Seed {seed} has been deleted.")
|
| 181 |
+
return display_seeds()
|
| 182 |
+
|
| 183 |
+
|
| 184 |
+
# 定义播放音频的函数
|
| 185 |
+
def do_play_seed(val):
|
| 186 |
+
# 从 val 匹配 [(\d+)] 获取index
|
| 187 |
+
index = re.search(r'\[(\d+)\]', val)
|
| 188 |
+
if index:
|
| 189 |
+
index = int(index.group(1))
|
| 190 |
+
seed = saved_seeds[index]['seed']
|
| 191 |
+
audio_path = saved_seeds[index]['path']
|
| 192 |
+
if audio_path:
|
| 193 |
+
return gr.update(visible=True, value=audio_path)
|
| 194 |
+
return gr.update(visible=False, value=None)
|
| 195 |
+
|
| 196 |
+
|
| 197 |
+
def seed_change_btn():
|
| 198 |
+
global SELECTED_SEED_INDEX
|
| 199 |
+
if SELECTED_SEED_INDEX == -1:
|
| 200 |
+
return ['删除', '试听']
|
| 201 |
+
return [f'删除 idx=[{SELECTED_SEED_INDEX[0]}]', f'试听 idx=[{SELECTED_SEED_INDEX[0]}]']
|
| 202 |
+
|
| 203 |
+
|
| 204 |
+
def audio_interface(num_seeds, texts, progress=gr.Progress()):
|
| 205 |
+
"""
|
| 206 |
+
生成音频
|
| 207 |
+
:param num_seeds:
|
| 208 |
+
:param texts:
|
| 209 |
+
:param progress:
|
| 210 |
+
:return:
|
| 211 |
+
"""
|
| 212 |
+
seeds = generate_seeds(num_seeds, texts, progress.tqdm)
|
| 213 |
+
wavs = [_[0] for _ in seeds]
|
| 214 |
+
seeds = [f"保存种子 {_[1]}" for _ in seeds]
|
| 215 |
+
# 不足的部分
|
| 216 |
+
all_wavs = wavs + [None] * (max_audio_components - len(wavs))
|
| 217 |
+
all_seeds = seeds + [''] * (max_audio_components - len(seeds))
|
| 218 |
+
return [item for pair in zip(all_wavs, all_seeds, all_wavs) for item in pair]
|
| 219 |
+
|
| 220 |
+
|
| 221 |
+
# 保存刚刚生成的种子文件路径
|
| 222 |
+
audio_paths = [gr.State(value=None) for _ in range(max_audio_components)]
|
| 223 |
+
|
| 224 |
+
|
| 225 |
+
def audio_interface_with_paths(num_seeds, texts, progress=gr.Progress()):
|
| 226 |
+
"""
|
| 227 |
+
比 audio_interface 多携带音频的 path
|
| 228 |
+
"""
|
| 229 |
+
results = audio_interface(num_seeds, texts, progress)
|
| 230 |
+
wavs = results[::2] # 提取音频文件路径
|
| 231 |
+
for i, wav in enumerate(wavs):
|
| 232 |
+
audio_paths[i].value = wav # 直接为 State 组件赋值
|
| 233 |
+
return results
|
| 234 |
+
|
| 235 |
+
|
| 236 |
+
def audio_interface_empty(num_seeds, texts, progress=gr.Progress(track_tqdm=True)):
|
| 237 |
+
return [None, "", None] * max_audio_components
|
| 238 |
+
|
| 239 |
+
|
| 240 |
+
def update_audio_components(slider_value):
|
| 241 |
+
# 根据滑块的值更新 Audio 组件的可见性
|
| 242 |
+
k = int(slider_value)
|
| 243 |
+
audios = [gr.Audio(visible=True)] * k + [gr.Audio(visible=False)] * (max_audio_components - k)
|
| 244 |
+
tbs = [gr.Textbox(visible=True)] * k + [gr.Textbox(visible=False)] * (max_audio_components - k)
|
| 245 |
+
stats = [gr.State(value=None)] * max_audio_components
|
| 246 |
+
print(f'k={k}, audios={len(audios)}')
|
| 247 |
+
return [item for pair in zip(audios, tbs, stats) for item in pair]
|
| 248 |
+
|
| 249 |
+
|
| 250 |
+
def seed_change(evt: gr.SelectData):
|
| 251 |
+
# print(f"You selected {evt.value} at {evt.index} from {evt.target}")
|
| 252 |
+
global SELECTED_SEED_INDEX
|
| 253 |
+
SELECTED_SEED_INDEX = evt.index
|
| 254 |
+
return evt.index
|
| 255 |
+
|
| 256 |
+
|
| 257 |
+
def generate_tts_audio(text_file, num_seeds, seed, speed, oral, laugh, bk, min_length, batch_size, temperature, top_P,
|
| 258 |
+
top_K, roleid=None, refine_text=True, speaker_type="seed", pt_file=None, progress=gr.Progress()):
|
| 259 |
+
from tts_model import generate_audio_for_seed
|
| 260 |
+
from utils import split_text, replace_tokens, restore_tokens
|
| 261 |
+
if seed in [0, -1, None]:
|
| 262 |
+
seed = random.randint(1, 9999)
|
| 263 |
+
content = ''
|
| 264 |
+
if os.path.isfile(text_file):
|
| 265 |
+
content = ""
|
| 266 |
+
elif isinstance(text_file, str):
|
| 267 |
+
content = text_file
|
| 268 |
+
# 将 [uv_break] [laugh] 替换为 _uv_break_ _laugh_ 处理后再还原
|
| 269 |
+
content = replace_tokens(content)
|
| 270 |
+
texts = split_text(content, min_length=min_length)
|
| 271 |
+
for i, text in enumerate(texts):
|
| 272 |
+
texts[i] = restore_tokens(text)
|
| 273 |
+
|
| 274 |
+
if oral < 0 or oral > 9 or laugh < 0 or laugh > 2 or bk < 0 or bk > 7:
|
| 275 |
+
raise ValueError("oral_(0-9), laugh_(0-2), break_(0-7) out of range")
|
| 276 |
+
|
| 277 |
+
refine_text_prompt = f"[oral_{oral}][laugh_{laugh}][break_{bk}]"
|
| 278 |
+
try:
|
| 279 |
+
output_files = generate_audio_for_seed(
|
| 280 |
+
chat=chat,
|
| 281 |
+
seed=seed,
|
| 282 |
+
texts=texts,
|
| 283 |
+
batch_size=batch_size,
|
| 284 |
+
speed=speed,
|
| 285 |
+
refine_text_prompt=refine_text_prompt,
|
| 286 |
+
roleid=roleid,
|
| 287 |
+
temperature=temperature,
|
| 288 |
+
top_P=top_P,
|
| 289 |
+
top_K=top_K,
|
| 290 |
+
cur_tqdm=progress.tqdm,
|
| 291 |
+
skip_save=False,
|
| 292 |
+
skip_refine_text=not refine_text,
|
| 293 |
+
speaker_type=speaker_type,
|
| 294 |
+
pt_file=pt_file,
|
| 295 |
+
)
|
| 296 |
+
return output_files
|
| 297 |
+
except Exception as e:
|
| 298 |
+
raise e
|
| 299 |
+
|
| 300 |
+
|
| 301 |
+
def generate_tts_audio_stream(text_file, num_seeds, seed, speed, oral, laugh, bk, min_length, batch_size, temperature,
|
| 302 |
+
top_P,
|
| 303 |
+
top_K, roleid=None, refine_text=True, speaker_type="seed", pt_file=None,
|
| 304 |
+
stream_mode="fake"):
|
| 305 |
+
from utils import split_text, replace_tokens, restore_tokens
|
| 306 |
+
from tts_model import deterministic
|
| 307 |
+
if seed in [0, -1, None]:
|
| 308 |
+
seed = random.randint(1, 9999)
|
| 309 |
+
content = ''
|
| 310 |
+
if os.path.isfile(text_file):
|
| 311 |
+
content = ""
|
| 312 |
+
elif isinstance(text_file, str):
|
| 313 |
+
content = text_file
|
| 314 |
+
# 将 [uv_break] [laugh] 替换为 _uv_break_ _laugh_ 处理后再还原
|
| 315 |
+
content = replace_tokens(content)
|
| 316 |
+
# texts = [normalize_zh(_) for _ in content.split('\n') if _.strip()]
|
| 317 |
+
texts = split_text(content, min_length=min_length)
|
| 318 |
+
|
| 319 |
+
for i, text in enumerate(texts):
|
| 320 |
+
texts[i] = restore_tokens(text)
|
| 321 |
+
|
| 322 |
+
if oral < 0 or oral > 9 or laugh < 0 or laugh > 2 or bk < 0 or bk > 7:
|
| 323 |
+
raise ValueError("oral_(0-9), laugh_(0-2), break_(0-7) out of range")
|
| 324 |
+
|
| 325 |
+
refine_text_prompt = f"[oral_{oral}][laugh_{laugh}][break_{bk}]"
|
| 326 |
+
|
| 327 |
+
print(f"speaker_type: {speaker_type}")
|
| 328 |
+
if speaker_type == "seed":
|
| 329 |
+
if seed in [None, -1, 0, "", "random"]:
|
| 330 |
+
seed = np.random.randint(0, 9999)
|
| 331 |
+
deterministic(seed)
|
| 332 |
+
rnd_spk_emb = chat.sample_random_speaker()
|
| 333 |
+
elif speaker_type == "role":
|
| 334 |
+
# 从 JSON 文件中读取数据
|
| 335 |
+
with open('./slct_voice_240605.json', 'r', encoding='utf-8') as json_file:
|
| 336 |
+
slct_idx_loaded = json.load(json_file)
|
| 337 |
+
# 将包含 Tensor 数据的部分转换回 Tensor 对象
|
| 338 |
+
for key in slct_idx_loaded:
|
| 339 |
+
tensor_list = slct_idx_loaded[key]["tensor"]
|
| 340 |
+
slct_idx_loaded[key]["tensor"] = torch.tensor(tensor_list)
|
| 341 |
+
# 将音色 tensor 打包进params_infer_code，固定使用此音色发音，调低temperature
|
| 342 |
+
rnd_spk_emb = slct_idx_loaded[roleid]["tensor"]
|
| 343 |
+
# temperature = 0.001
|
| 344 |
+
elif speaker_type == "pt":
|
| 345 |
+
print(pt_file)
|
| 346 |
+
rnd_spk_emb = torch.load(pt_file)
|
| 347 |
+
print(rnd_spk_emb.shape)
|
| 348 |
+
if rnd_spk_emb.shape != (768,):
|
| 349 |
+
raise ValueError("维度应为 768。")
|
| 350 |
+
else:
|
| 351 |
+
raise ValueError(f"Invalid speaker_type: {speaker_type}. ")
|
| 352 |
+
|
| 353 |
+
params_infer_code = {
|
| 354 |
+
'spk_emb': rnd_spk_emb,
|
| 355 |
+
'prompt': f'[speed_{speed}]',
|
| 356 |
+
'top_P': top_P,
|
| 357 |
+
'top_K': top_K,
|
| 358 |
+
'temperature': temperature
|
| 359 |
+
}
|
| 360 |
+
params_refine_text = {
|
| 361 |
+
'prompt': refine_text_prompt,
|
| 362 |
+
'top_P': top_P,
|
| 363 |
+
'top_K': top_K,
|
| 364 |
+
'temperature': temperature
|
| 365 |
+
}
|
| 366 |
+
|
| 367 |
+
if stream_mode == "real":
|
| 368 |
+
for text in texts:
|
| 369 |
+
_params_infer_code = {**params_infer_code}
|
| 370 |
+
wavs_gen = chat.infer(text, params_infer_code=_params_infer_code, params_refine_text=params_refine_text,
|
| 371 |
+
use_decoder=True, skip_refine_text=True, stream=True)
|
| 372 |
+
for gen in wavs_gen:
|
| 373 |
+
wavs = [np.array([[]])]
|
| 374 |
+
wavs[0] = np.hstack([wavs[0], np.array(gen[0])])
|
| 375 |
+
audio = wavs[0][0]
|
| 376 |
+
yield 24000, normalize_audio(audio)
|
| 377 |
+
|
| 378 |
+
clear_cuda_cache()
|
| 379 |
+
else:
|
| 380 |
+
for text in batch_split(texts, batch_size):
|
| 381 |
+
_params_infer_code = {**params_infer_code}
|
| 382 |
+
wavs = chat.infer(text, params_infer_code=_params_infer_code, params_refine_text=params_refine_text,
|
| 383 |
+
use_decoder=True, skip_refine_text=False, stream=False)
|
| 384 |
+
combined_audio = combine_audio(wavs)
|
| 385 |
+
yield 24000, combined_audio[0]
|
| 386 |
+
|
| 387 |
+
|
| 388 |
+
def generate_refine(text_file, oral, laugh, bk, temperature, top_P, top_K, progress=gr.Progress()):
|
| 389 |
+
from tts_model import generate_refine_text
|
| 390 |
+
from utils import split_text, replace_tokens, restore_tokens, replace_space_between_chinese
|
| 391 |
+
seed = random.randint(1, 9999)
|
| 392 |
+
refine_text_prompt = f"[oral_{oral}][laugh_{laugh}][break_{bk}]"
|
| 393 |
+
content = ''
|
| 394 |
+
if os.path.isfile(text_file):
|
| 395 |
+
content = ""
|
| 396 |
+
elif isinstance(text_file, str):
|
| 397 |
+
content = text_file
|
| 398 |
+
if re.search(r'\[uv_break\]|\[laugh\]', content) is not None:
|
| 399 |
+
gr.Info("检测到 [uv_break] [laugh]，不能重复 refine ")
|
| 400 |
+
# print("检测到 [uv_break] [laugh]，不能重复 refine ")
|
| 401 |
+
return content
|
| 402 |
+
batch_size = 5
|
| 403 |
+
|
| 404 |
+
content = replace_tokens(content)
|
| 405 |
+
texts = split_text(content, min_length=120)
|
| 406 |
+
print(texts)
|
| 407 |
+
for i, text in enumerate(texts):
|
| 408 |
+
texts[i] = restore_tokens(text)
|
| 409 |
+
txts = []
|
| 410 |
+
for batch in progress.tqdm(batch_split(texts, batch_size), desc=f"Refine Text Please Wait ..."):
|
| 411 |
+
txts.extend(generate_refine_text(chat, seed, batch, refine_text_prompt, temperature, top_P, top_K))
|
| 412 |
+
return replace_space_between_chinese('\n\n'.join(txts))
|
| 413 |
+
|
| 414 |
+
|
| 415 |
+
def generate_seed():
|
| 416 |
+
new_seed = random.randint(1, 9999)
|
| 417 |
+
return {
|
| 418 |
+
"__type__": "update",
|
| 419 |
+
"value": new_seed
|
| 420 |
+
}
|
| 421 |
+
|
| 422 |
+
|
| 423 |
+
def update_label(text):
|
| 424 |
+
word_count = len(text)
|
| 425 |
+
return gr.update(label=f"朗读文本（{word_count} 字）")
|
| 426 |
+
|
| 427 |
+
|
| 428 |
+
def inser_token(text, btn):
|
| 429 |
+
if btn == "+笑声":
|
| 430 |
+
return gr.update(
|
| 431 |
+
value=text + "[laugh]"
|
| 432 |
+
)
|
| 433 |
+
elif btn == "+停顿":
|
| 434 |
+
return gr.update(
|
| 435 |
+
value=text + "[uv_break]"
|
| 436 |
+
)
|
| 437 |
+
|
| 438 |
+
|
| 439 |
+
with gr.Blocks() as demo:
|
| 440 |
+
# 项目链接
|
| 441 |
+
gr.Markdown("""
|
| 442 |
+
<div style='text-align: center; font-size: 16px;'>
|
| 443 |
+
🌟 <a href='https://github.com/6drf21e/ChatTTS_colab'>项目地址 欢迎 start</a> 🌟
|
| 444 |
+
</div>
|
| 445 |
+
""")
|
| 446 |
+
|
| 447 |
+
with gr.Tab("音色抽卡"):
|
| 448 |
+
with gr.Row():
|
| 449 |
+
with gr.Column(scale=1):
|
| 450 |
+
texts = [
|
| 451 |
+
"四川美食确实以辣闻名，但也有不辣的选择。比如甜水面、赖汤圆、蛋烘糕、叶儿粑等，这些小吃口味温和，甜而不腻，也很受欢迎。",
|
| 452 |
+
"我是一个充满活力的人，喜欢运动，喜欢旅行，喜欢尝试新鲜事物。我喜欢挑战自己，不断突破自己的极限，让自己变得更加强大。",
|
| 453 |
+
"罗森宣布将于7月24日退市，在华门店超6000家！",
|
| 454 |
+
]
|
| 455 |
+
# gr.Markdown("### 随机音色抽卡")
|
| 456 |
+
gr.Markdown("""
|
| 457 |
+
免抽卡，直接找稳定音色👇
|
| 458 |
+
|
| 459 |
+
[ModelScope ChatTTS Speaker(国内)](https://modelscope.cn/studios/ttwwwaa/ChatTTS_Speaker) | [HuggingFace ChatTTS Speaker(国外)](https://huggingface.co/spaces/taa/ChatTTS_Speaker)
|
| 460 |
+
|
| 461 |
+
在相同的 seed 和 温度等参数下，音色具有一定的一致性。点击下面的“随机音色生成”按钮将生成多个 seed。找到满意的音色后，点击音频下方“保存”按钮。
|
| 462 |
+
**注意：不同机器使用相同种子生成的音频音色可能不同，同一机器使用相同种子多次生成的音频音色也可能变化。**
|
| 463 |
+
""")
|
| 464 |
+
input_text = gr.Textbox(label="测试文本",
|
| 465 |
+
info="**每行文本**都会生成一段音频，最终输出的音频是将这些音频段合成后的结果。建议使用**多行文本**进行测试，以确保音色稳定性。",
|
| 466 |
+
lines=4, placeholder="请输入文本...", value='\n'.join(texts))
|
| 467 |
+
|
| 468 |
+
num_seeds = gr.Slider(minimum=1, maximum=max_audio_components, step=1, label="seed生成数量",
|
| 469 |
+
value=num_seeds_default)
|
| 470 |
+
|
| 471 |
+
generate_button = gr.Button("随机音色抽卡🎲", variant="primary")
|
| 472 |
+
|
| 473 |
+
# 保存的种子
|
| 474 |
+
gr.Markdown("### 种子管理界面")
|
| 475 |
+
seed_list = gr.DataFrame(
|
| 476 |
+
label="种子列表",
|
| 477 |
+
headers=["Index", "Seed", "Name", "Path"],
|
| 478 |
+
datatype=["number", "number", "str", "str"],
|
| 479 |
+
interactive=True,
|
| 480 |
+
col_count=(4, "fixed"),
|
| 481 |
+
value=display_seeds
|
| 482 |
+
)
|
| 483 |
+
|
| 484 |
+
with gr.Row():
|
| 485 |
+
refresh_button = gr.Button("刷新")
|
| 486 |
+
save_button = gr.Button("保存")
|
| 487 |
+
del_button = gr.Button("删除")
|
| 488 |
+
play_button = gr.Button("试听")
|
| 489 |
+
|
| 490 |
+
with gr.Row():
|
| 491 |
+
# 添加已保存的种子音频播放组件
|
| 492 |
+
audio_player = gr.Audio(label="播放已保存种子音频", visible=False)
|
| 493 |
+
|
| 494 |
+
# 绑定按钮和函数
|
| 495 |
+
refresh_button.click(display_seeds, outputs=seed_list)
|
| 496 |
+
seed_list.select(seed_change).success(seed_change_btn, outputs=[del_button, play_button])
|
| 497 |
+
save_button.click(do_save_seeds, inputs=[seed_list], outputs=None)
|
| 498 |
+
del_button.click(do_delete_seed, inputs=del_button, outputs=seed_list)
|
| 499 |
+
play_button.click(do_play_seed, inputs=play_button, outputs=audio_player)
|
| 500 |
+
|
| 501 |
+
with gr.Column(scale=1):
|
| 502 |
+
audio_components = []
|
| 503 |
+
for i in range(max_audio_components):
|
| 504 |
+
visible = i < num_seeds_default
|
| 505 |
+
a = gr.Audio(f"Audio {i}", visible=visible)
|
| 506 |
+
t = gr.Button(f"Seed", visible=visible)
|
| 507 |
+
s = gr.State(value=None)
|
| 508 |
+
t.click(do_save_seed, inputs=[t, s], outputs=None).success(display_seeds, outputs=seed_list)
|
| 509 |
+
audio_components.append(a)
|
| 510 |
+
audio_components.append(t)
|
| 511 |
+
audio_components.append(s)
|
| 512 |
+
|
| 513 |
+
num_seeds.change(update_audio_components, inputs=num_seeds, outputs=audio_components)
|
| 514 |
+
# output = gr.Column()
|
| 515 |
+
# audio = gr.Audio(label="Output Audio")
|
| 516 |
+
|
| 517 |
+
generate_button.click(
|
| 518 |
+
audio_interface_empty,
|
| 519 |
+
inputs=[num_seeds, input_text],
|
| 520 |
+
outputs=audio_components
|
| 521 |
+
).success(audio_interface, inputs=[num_seeds, input_text], outputs=audio_components)
|
| 522 |
+
with gr.Tab("长音频生成"):
|
| 523 |
+
with gr.Row():
|
| 524 |
+
with gr.Column():
|
| 525 |
+
gr.Markdown("### 文本")
|
| 526 |
+
# gr.Markdown("请上传要转换的文本文件（.txt 格式）。")
|
| 527 |
+
# text_file_input = gr.File(label="文本文件", file_types=[".txt"])
|
| 528 |
+
default_text = "四川美食确实以辣闻名，但也有不辣的选择。比如甜水面、赖汤圆、蛋烘糕、叶儿粑等，这些小吃口味温和，甜而不腻，也很受欢迎。"
|
| 529 |
+
text_file_input = gr.Textbox(label=f"朗读文本（字数: {len(default_text)}）", lines=4,
|
| 530 |
+
placeholder="Please Input Text...", value=default_text)
|
| 531 |
+
# 当文本框内容发生变化时调用 update_label 函数
|
| 532 |
+
text_file_input.change(update_label, inputs=text_file_input, outputs=text_file_input)
|
| 533 |
+
# 加入停顿按钮
|
| 534 |
+
with gr.Row():
|
| 535 |
+
break_button = gr.Button("+停顿", variant="secondary")
|
| 536 |
+
laugh_button = gr.Button("+笑声", variant="secondary")
|
| 537 |
+
refine_button = gr.Button("Refine Text（预处理 加入停顿词、笑声等）", variant="secondary")
|
| 538 |
+
|
| 539 |
+
with gr.Column():
|
| 540 |
+
gr.Markdown("### 配置参数")
|
| 541 |
+
with gr.Row():
|
| 542 |
+
with gr.Column():
|
| 543 |
+
gr.Markdown("音色选择")
|
| 544 |
+
num_seeds_input = gr.Number(label="生成音频的数量", value=1, precision=0, visible=False)
|
| 545 |
+
speaker_stat = gr.State(value="seed")
|
| 546 |
+
tab_seed = gr.Tab(label="种子")
|
| 547 |
+
with tab_seed:
|
| 548 |
+
with gr.Row():
|
| 549 |
+
seed_input = gr.Number(label="指定种子", info="种子决定音色 0则随机", value=None,
|
| 550 |
+
precision=0)
|
| 551 |
+
generate_audio_seed = gr.Button("\U0001F3B2")
|
| 552 |
+
tab_roleid = gr.Tab(label="内置音色")
|
| 553 |
+
with tab_roleid:
|
| 554 |
+
roleid_input = gr.Dropdown(label="内置音色",
|
| 555 |
+
choices=[("发姐", "1"),
|
| 556 |
+
("纯情男大学生", "2"),
|
| 557 |
+
("阳光开朗大男孩", "3"),
|
| 558 |
+
("知心小姐姐", "4"),
|
| 559 |
+
("电视台女主持", "5"),
|
| 560 |
+
("魅力大叔", "6"),
|
| 561 |
+
("优雅甜美", "7"),
|
| 562 |
+
("贴心男宝2", "21"),
|
| 563 |
+
("正式打工人", "8"),
|
| 564 |
+
("贴心男宝1", "9")],
|
| 565 |
+
value="1",
|
| 566 |
+
info="选择音色后会覆盖种子。感谢 @QuantumDriver 提供音色")
|
| 567 |
+
tab_pt = gr.Tab(label="上传.PT文件")
|
| 568 |
+
with tab_pt:
|
| 569 |
+
pt_input = gr.File(label="上传音色文件", file_types=[".pt"], height=100)
|
| 570 |
+
|
| 571 |
+
with gr.Row():
|
| 572 |
+
style_select = gr.Radio(label="预设参数", info="语速部分可自行更改",
|
| 573 |
+
choices=["小说朗读", "对话", "中英混合", "默认"], value="默认",
|
| 574 |
+
interactive=True, )
|
| 575 |
+
with gr.Row():
|
| 576 |
+
# refine
|
| 577 |
+
refine_text_input = gr.Checkbox(label="Refine",
|
| 578 |
+
info="打开后会自动根据下方参数添加笑声/停顿等。关闭后可自行添加 [uv_break] [laugh] 或者点击下方 Refin按钮先行转换",
|
| 579 |
+
value=True)
|
| 580 |
+
speed_input = gr.Slider(label="语速", minimum=1, maximum=10, value=DEFAULT_SPEED, step=1)
|
| 581 |
+
with gr.Row():
|
| 582 |
+
oral_input = gr.Slider(label="口语化", minimum=0, maximum=9, value=DEFAULT_ORAL, step=1)
|
| 583 |
+
laugh_input = gr.Slider(label="笑声", minimum=0, maximum=2, value=DEFAULT_LAUGH, step=1)
|
| 584 |
+
bk_input = gr.Slider(label="停顿", minimum=0, maximum=7, value=DEFAULT_BK, step=1)
|
| 585 |
+
# gr.Markdown("### 文本参数")
|
| 586 |
+
with gr.Row():
|
| 587 |
+
min_length_input = gr.Number(label="文本分段长度", info="大于这个数值进行分段",
|
| 588 |
+
value=DEFAULT_SEG_LENGTH, precision=0)
|
| 589 |
+
batch_size_input = gr.Number(label="批大小", info="越高越快 太高爆显存 4G推荐3 其他酌情",
|
| 590 |
+
value=DEFAULT_BATCH_SIZE, precision=0)
|
| 591 |
+
with gr.Accordion("其他参数", open=False):
|
| 592 |
+
with gr.Row():
|
| 593 |
+
# 温度 top_P top_K
|
| 594 |
+
temperature_input = gr.Slider(label="温度", minimum=0.01, maximum=1.0, step=0.01,
|
| 595 |
+
value=DEFAULT_TEMPERATURE)
|
| 596 |
+
top_P_input = gr.Slider(label="top_P", minimum=0.1, maximum=0.9, step=0.05, value=DEFAULT_TOP_P)
|
| 597 |
+
top_K_input = gr.Slider(label="top_K", minimum=1, maximum=20, step=1, value=DEFAULT_TOP_K)
|
| 598 |
+
# reset 按钮
|
| 599 |
+
reset_button = gr.Button("重置")
|
| 600 |
+
|
| 601 |
+
with gr.Row():
|
| 602 |
+
with gr.Column():
|
| 603 |
+
generate_button = gr.Button("生成音频", variant="primary")
|
| 604 |
+
with gr.Column():
|
| 605 |
+
generate_button_stream = gr.Button("流式生成音频(一边播放一边推理)", variant="primary")
|
| 606 |
+
stream_select = gr.Radio(label="流输出方式",
|
| 607 |
+
info="真流式为实验功能，播放效果：卡播卡播卡播（⏳🎵⏳🎵⏳🎵）；伪流式为分段推理后输出，播放效果：卡卡卡播播播播（⏳⏳🎵🎵🎵🎵）。伪流式批次建议4以上减少卡顿",
|
| 608 |
+
choices=[("真", "real"), ("伪", "fake")], value="fake", interactive=True, )
|
| 609 |
+
|
| 610 |
+
with gr.Row():
|
| 611 |
+
output_audio = gr.Audio(label="生成的音频文件")
|
| 612 |
+
output_audio_stream = gr.Audio(label="流式音频", value=None,
|
| 613 |
+
streaming=True,
|
| 614 |
+
autoplay=True,
|
| 615 |
+
# disable auto play for Windows, due to https://developer.chrome.com/blog/autoplay#webaudio
|
| 616 |
+
interactive=False,
|
| 617 |
+
show_label=True)
|
| 618 |
+
|
| 619 |
+
generate_audio_seed.click(generate_seed,
|
| 620 |
+
inputs=[],
|
| 621 |
+
outputs=seed_input)
|
| 622 |
+
|
| 623 |
+
|
| 624 |
+
def do_tab_change(evt: gr.SelectData):
|
| 625 |
+
print(evt.selected, evt.index, evt.value, evt.target)
|
| 626 |
+
kv = {
|
| 627 |
+
"种子": "seed",
|
| 628 |
+
"内置音色": "role",
|
| 629 |
+
"上传.PT文件": "pt"
|
| 630 |
+
}
|
| 631 |
+
return kv.get(evt.value, "seed")
|
| 632 |
+
|
| 633 |
+
|
| 634 |
+
tab_seed.select(do_tab_change, outputs=speaker_stat)
|
| 635 |
+
tab_roleid.select(do_tab_change, outputs=speaker_stat)
|
| 636 |
+
tab_pt.select(do_tab_change, outputs=speaker_stat)
|
| 637 |
+
|
| 638 |
+
|
| 639 |
+
def do_style_select(x):
|
| 640 |
+
if x == "小说朗读":
|
| 641 |
+
return [4, 0, 0, 2]
|
| 642 |
+
elif x == "对话":
|
| 643 |
+
return [5, 5, 1, 4]
|
| 644 |
+
elif x == "中英混合":
|
| 645 |
+
return [4, 1, 0, 3]
|
| 646 |
+
else:
|
| 647 |
+
return [DEFAULT_SPEED, DEFAULT_ORAL, DEFAULT_LAUGH, DEFAULT_BK]
|
| 648 |
+
|
| 649 |
+
|
| 650 |
+
# style_select 选择
|
| 651 |
+
style_select.change(
|
| 652 |
+
do_style_select,
|
| 653 |
+
inputs=style_select,
|
| 654 |
+
outputs=[speed_input, oral_input, laugh_input, bk_input]
|
| 655 |
+
)
|
| 656 |
+
|
| 657 |
+
# refine 按钮
|
| 658 |
+
refine_button.click(
|
| 659 |
+
generate_refine,
|
| 660 |
+
inputs=[text_file_input, oral_input, laugh_input, bk_input, temperature_input, top_P_input, top_K_input],
|
| 661 |
+
outputs=text_file_input
|
| 662 |
+
)
|
| 663 |
+
# 重置按钮 重置温度等参数
|
| 664 |
+
reset_button.click(
|
| 665 |
+
lambda: [0.3, 0.7, 20],
|
| 666 |
+
inputs=None,
|
| 667 |
+
outputs=[temperature_input, top_P_input, top_K_input]
|
| 668 |
+
)
|
| 669 |
+
|
| 670 |
+
generate_button.click(
|
| 671 |
+
fn=generate_tts_audio,
|
| 672 |
+
inputs=[
|
| 673 |
+
text_file_input,
|
| 674 |
+
num_seeds_input,
|
| 675 |
+
seed_input,
|
| 676 |
+
speed_input,
|
| 677 |
+
oral_input,
|
| 678 |
+
laugh_input,
|
| 679 |
+
bk_input,
|
| 680 |
+
min_length_input,
|
| 681 |
+
batch_size_input,
|
| 682 |
+
temperature_input,
|
| 683 |
+
top_P_input,
|
| 684 |
+
top_K_input,
|
| 685 |
+
roleid_input,
|
| 686 |
+
refine_text_input,
|
| 687 |
+
speaker_stat,
|
| 688 |
+
pt_input
|
| 689 |
+
],
|
| 690 |
+
outputs=[output_audio]
|
| 691 |
+
)
|
| 692 |
+
|
| 693 |
+
generate_button_stream.click(
|
| 694 |
+
fn=generate_tts_audio_stream,
|
| 695 |
+
inputs=[
|
| 696 |
+
text_file_input,
|
| 697 |
+
num_seeds_input,
|
| 698 |
+
seed_input,
|
| 699 |
+
speed_input,
|
| 700 |
+
oral_input,
|
| 701 |
+
laugh_input,
|
| 702 |
+
bk_input,
|
| 703 |
+
min_length_input,
|
| 704 |
+
batch_size_input,
|
| 705 |
+
temperature_input,
|
| 706 |
+
top_P_input,
|
| 707 |
+
top_K_input,
|
| 708 |
+
roleid_input,
|
| 709 |
+
refine_text_input,
|
| 710 |
+
speaker_stat,
|
| 711 |
+
pt_input,
|
| 712 |
+
stream_select
|
| 713 |
+
],
|
| 714 |
+
outputs=[output_audio_stream]
|
| 715 |
+
)
|
| 716 |
+
|
| 717 |
+
break_button.click(
|
| 718 |
+
inser_token,
|
| 719 |
+
inputs=[text_file_input, break_button],
|
| 720 |
+
outputs=text_file_input
|
| 721 |
+
)
|
| 722 |
+
|
| 723 |
+
laugh_button.click(
|
| 724 |
+
inser_token,
|
| 725 |
+
inputs=[text_file_input, laugh_button],
|
| 726 |
+
outputs=text_file_input
|
| 727 |
+
)
|
| 728 |
+
|
| 729 |
+
with gr.Tab("角色扮演"):
|
| 730 |
+
def txt_2_script(text):
|
| 731 |
+
lines = text.split("\n")
|
| 732 |
+
data = []
|
| 733 |
+
for line in lines:
|
| 734 |
+
if not line.strip():
|
| 735 |
+
continue
|
| 736 |
+
parts = line.split("::")
|
| 737 |
+
if len(parts) != 2:
|
| 738 |
+
continue
|
| 739 |
+
data.append({
|
| 740 |
+
"character": parts[0],
|
| 741 |
+
"txt": parts[1]
|
| 742 |
+
})
|
| 743 |
+
return data
|
| 744 |
+
|
| 745 |
+
|
| 746 |
+
def script_2_txt(data):
|
| 747 |
+
assert isinstance(data, list)
|
| 748 |
+
result = []
|
| 749 |
+
for item in data:
|
| 750 |
+
txt = item['txt'].replace('\n', ' ')
|
| 751 |
+
result.append(f"{item['character']}::{txt}")
|
| 752 |
+
return "\n".join(result)
|
| 753 |
+
|
| 754 |
+
|
| 755 |
+
def get_characters(lines):
|
| 756 |
+
assert isinstance(lines, list)
|
| 757 |
+
characters = list([_["character"] for _ in lines])
|
| 758 |
+
unique_characters = list(dict.fromkeys(characters))
|
| 759 |
+
print([[character, 0] for character in unique_characters])
|
| 760 |
+
return [[character, 0, 5, 2, 0, 4] for character in unique_characters]
|
| 761 |
+
|
| 762 |
+
|
| 763 |
+
def get_txt_characters(text):
|
| 764 |
+
return get_characters(txt_2_script(text))
|
| 765 |
+
|
| 766 |
+
|
| 767 |
+
def llm_change(model):
|
| 768 |
+
llm_setting = {
|
| 769 |
+
"gpt-3.5-turbo-0125": ["https://api.openai.com/v1"],
|
| 770 |
+
"gpt-4o": ["https://api.openai.com/v1"],
|
| 771 |
+
"deepseek-chat": ["https://api.deepseek.com"],
|
| 772 |
+
"yi-large": ["https://api.lingyiwanwu.com/v1"]
|
| 773 |
+
}
|
| 774 |
+
if model in llm_setting:
|
| 775 |
+
return llm_setting[model][0]
|
| 776 |
+
else:
|
| 777 |
+
gr.Error("Model not found.")
|
| 778 |
+
return None
|
| 779 |
+
|
| 780 |
+
|
| 781 |
+
def ai_script_generate(model, api_base, api_key, text, progress=gr.Progress(track_tqdm=True)):
|
| 782 |
+
from llm_utils import llm_operation
|
| 783 |
+
from config import LLM_PROMPT
|
| 784 |
+
scripts = llm_operation(api_base, api_key, model, LLM_PROMPT, text, required_keys=["txt", "character"])
|
| 785 |
+
return script_2_txt(scripts)
|
| 786 |
+
|
| 787 |
+
|
| 788 |
+
def generate_script_audio(text, models_seeds, progress=gr.Progress()):
|
| 789 |
+
scripts = txt_2_script(text) # 将文本转换为剧本
|
| 790 |
+
characters = get_characters(scripts) # 从剧本中提取角色
|
| 791 |
+
|
| 792 |
+
#
|
| 793 |
+
import pandas as pd
|
| 794 |
+
from collections import defaultdict
|
| 795 |
+
import itertools
|
| 796 |
+
from tts_model import generate_audio_for_seed
|
| 797 |
+
from utils import combine_audio, save_audio, normalize_zh
|
| 798 |
+
|
| 799 |
+
assert isinstance(models_seeds, pd.DataFrame)
|
| 800 |
+
|
| 801 |
+
# 批次处理函数
|
| 802 |
+
def batch(iterable, batch_size):
|
| 803 |
+
it = iter(iterable)
|
| 804 |
+
while True:
|
| 805 |
+
batch = list(itertools.islice(it, batch_size))
|
| 806 |
+
if not batch:
|
| 807 |
+
break
|
| 808 |
+
yield batch
|
| 809 |
+
|
| 810 |
+
column_mapping = {
|
| 811 |
+
'角色': 'character',
|
| 812 |
+
'种子': 'seed',
|
| 813 |
+
'语速': 'speed',
|
| 814 |
+
'口语': 'oral',
|
| 815 |
+
'笑声': 'laugh',
|
| 816 |
+
'停顿': 'break'
|
| 817 |
+
}
|
| 818 |
+
# 使用 rename 方法重命名 DataFrame 的列
|
| 819 |
+
models_seeds = models_seeds.rename(columns=column_mapping).to_dict(orient='records')
|
| 820 |
+
# models_seeds = models_seeds.to_dict(orient='records')
|
| 821 |
+
|
| 822 |
+
# 检查每个角色是否都有对应的种子
|
| 823 |
+
print(models_seeds)
|
| 824 |
+
seed_lookup = {seed['character']: seed for seed in models_seeds}
|
| 825 |
+
|
| 826 |
+
character_seeds = {}
|
| 827 |
+
missing_seeds = []
|
| 828 |
+
# 遍历所有角色
|
| 829 |
+
for character in characters:
|
| 830 |
+
character_name = character[0]
|
| 831 |
+
seed_info = seed_lookup.get(character_name)
|
| 832 |
+
if seed_info:
|
| 833 |
+
character_seeds[character_name] = seed_info
|
| 834 |
+
else:
|
| 835 |
+
missing_seeds.append(character_name)
|
| 836 |
+
|
| 837 |
+
if missing_seeds:
|
| 838 |
+
missing_characters_str = ', '.join(missing_seeds)
|
| 839 |
+
gr.Info(f"以下角色没有种子，请先设置种子：{missing_characters_str}")
|
| 840 |
+
return None
|
| 841 |
+
|
| 842 |
+
print(character_seeds)
|
| 843 |
+
# return
|
| 844 |
+
refine_text_prompt = "[oral_2][laugh_0][break_4]"
|
| 845 |
+
all_wavs = []
|
| 846 |
+
|
| 847 |
+
# 按角色分组，加速推理
|
| 848 |
+
grouped_lines = defaultdict(list)
|
| 849 |
+
for line in scripts:
|
| 850 |
+
grouped_lines[line["character"]].append(line)
|
| 851 |
+
|
| 852 |
+
batch_results = {character: [] for character in grouped_lines}
|
| 853 |
+
|
| 854 |
+
batch_size = 5 # 设置批次大小
|
| 855 |
+
# 按角色处理
|
| 856 |
+
for character, lines in progress.tqdm(grouped_lines.items(), desc="生成剧本音频"):
|
| 857 |
+
info = character_seeds[character]
|
| 858 |
+
seed = info["seed"]
|
| 859 |
+
speed = info["speed"]
|
| 860 |
+
orla = info["oral"]
|
| 861 |
+
laugh = info["laugh"]
|
| 862 |
+
bk = info["break"]
|
| 863 |
+
|
| 864 |
+
refine_text_prompt = f"[oral_{orla}][laugh_{laugh}][break_{bk}]"
|
| 865 |
+
|
| 866 |
+
# 按批次处理
|
| 867 |
+
for batch_lines in batch(lines, batch_size):
|
| 868 |
+
texts = [normalize_zh(line["txt"]) for line in batch_lines]
|
| 869 |
+
print(f"seed={seed} t={texts} c={character} s={speed} r={refine_text_prompt}")
|
| 870 |
+
wavs = generate_audio_for_seed(chat, int(seed), texts, DEFAULT_BATCH_SIZE, speed,
|
| 871 |
+
refine_text_prompt, None, DEFAULT_TEMPERATURE, DEFAULT_TOP_P,
|
| 872 |
+
DEFAULT_TOP_K, skip_save=True) # 批量处理文本
|
| 873 |
+
batch_results[character].extend(wavs)
|
| 874 |
+
|
| 875 |
+
# 转换回原排序
|
| 876 |
+
for line in scripts:
|
| 877 |
+
character = line["character"]
|
| 878 |
+
all_wavs.append(batch_results[character].pop(0))
|
| 879 |
+
|
| 880 |
+
# 合成所有音频
|
| 881 |
+
audio = combine_audio(all_wavs)
|
| 882 |
+
fname = f"script_{int(time.time())}.wav"
|
| 883 |
+
return save_audio(fname, audio)
|
| 884 |
+
|
| 885 |
+
|
| 886 |
+
script_example = {
|
| 887 |
+
"lines": [{
|
| 888 |
+
"txt": "在一个风和日丽的下午，小红帽准备去森林里看望她的奶奶。",
|
| 889 |
+
"character": "旁白"
|
| 890 |
+
}, {
|
| 891 |
+
"txt": "小红帽说",
|
| 892 |
+
"character": "旁白"
|
| 893 |
+
}, {
|
| 894 |
+
"txt": "我要给奶奶带点好吃的。",
|
| 895 |
+
"character": "年轻女性"
|
| 896 |
+
}, {
|
| 897 |
+
"txt": "在森林里，小红帽遇到了狡猾的大灰狼。",
|
| 898 |
+
"character": "旁白"
|
| 899 |
+
}, {
|
| 900 |
+
"txt": "大灰狼说",
|
| 901 |
+
"character": "旁白"
|
| 902 |
+
}, {
|
| 903 |
+
"txt": "小红帽，你的篮子里装的是什么？",
|
| 904 |
+
"character": "中年男性"
|
| 905 |
+
}, {
|
| 906 |
+
"txt": "小红帽回答",
|
| 907 |
+
"character": "旁白"
|
| 908 |
+
}, {
|
| 909 |
+
"txt": "这是给奶奶的蛋糕和果酱。",
|
| 910 |
+
"character": "年轻女性"
|
| 911 |
+
}, {
|
| 912 |
+
"txt": "大灰狼心生一计，决定先到奶奶家等待小红帽。",
|
| 913 |
+
"character": "旁白"
|
| 914 |
+
}, {
|
| 915 |
+
"txt": "当小红帽到达奶奶家时，她发现大灰狼伪装成了奶奶。",
|
| 916 |
+
"character": "旁白"
|
| 917 |
+
}, {
|
| 918 |
+
"txt": "小红帽疑惑的问",
|
| 919 |
+
"character": "旁白"
|
| 920 |
+
}, {
|
| 921 |
+
"txt": "奶奶，你的耳朵怎么这么尖？",
|
| 922 |
+
"character": "年轻女性"
|
| 923 |
+
}, {
|
| 924 |
+
"txt": "大灰狼慌张地回答",
|
| 925 |
+
"character": "旁白"
|
| 926 |
+
}, {
|
| 927 |
+
"txt": "哦，这是为了更好地听你说话。",
|
| 928 |
+
"character": "中年男性"
|
| 929 |
+
}, {
|
| 930 |
+
"txt": "小红帽越发觉得不对劲，最终发现了大灰狼的诡计。",
|
| 931 |
+
"character": "旁白"
|
| 932 |
+
}, {
|
| 933 |
+
"txt": "她大声呼救，森林里的猎人听到后赶来救了她和奶奶。",
|
| 934 |
+
"character": "旁白"
|
| 935 |
+
}, {
|
| 936 |
+
"txt": "从此，小红帽再也没有单独进入森林，而是和家人一起去看望奶奶。",
|
| 937 |
+
"character": "旁白"
|
| 938 |
+
}]
|
| 939 |
+
}
|
| 940 |
+
|
| 941 |
+
ai_text_default = "武侠小说《花木兰大战周树人》 要符合人物背景"
|
| 942 |
+
|
| 943 |
+
with gr.Row(equal_height=True):
|
| 944 |
+
with gr.Column(scale=2):
|
| 945 |
+
gr.Markdown("### AI脚本")
|
| 946 |
+
gr.Markdown("""
|
| 947 |
+
为确保生成效果稳定，仅支持与 GPT-4 相当的模型，推荐使用 4o yi-large deepseek。
|
| 948 |
+
如果没有反应，请检查日志中的错误信息。如果提示格式错误，请重试几次。国内模型可能会受到风控影响，建议更换文本内容后再试。
|
| 949 |
+
|
| 950 |
+
申请渠道（免费额度）：
|
| 951 |
+
|
| 952 |
+
- [https://platform.deepseek.com/](https://platform.deepseek.com/)
|
| 953 |
+
- [https://platform.lingyiwanwu.com/](https://platform.lingyiwanwu.com/)
|
| 954 |
+
|
| 955 |
+
""")
|
| 956 |
+
# 申请渠道
|
| 957 |
+
|
| 958 |
+
with gr.Row(equal_height=True):
|
| 959 |
+
# 选择模型 只有 gpt4o deepseek-chat yi-large 三个选项
|
| 960 |
+
model_select = gr.Radio(label="选择模型", choices=["gpt-4o", "deepseek-chat", "yi-large"],
|
| 961 |
+
value="gpt-4o", interactive=True, )
|
| 962 |
+
with gr.Row(equal_height=True):
|
| 963 |
+
openai_api_base_input = gr.Textbox(label="OpenAI API Base URL",
|
| 964 |
+
placeholder="请输入API Base URL",
|
| 965 |
+
value=r"https://api.openai.com/v1")
|
| 966 |
+
openai_api_key_input = gr.Textbox(label="OpenAI API Key", placeholder="请输入API Key",
|
| 967 |
+
value="sk-xxxxxxx", type="password")
|
| 968 |
+
# AI提示词
|
| 969 |
+
ai_text_input = gr.Textbox(label="剧情简介或者一段故事", placeholder="请输入文本...", lines=2,
|
| 970 |
+
value=ai_text_default)
|
| 971 |
+
|
| 972 |
+
# 生成脚本的按钮
|
| 973 |
+
ai_script_generate_button = gr.Button("AI脚本生成")
|
| 974 |
+
|
| 975 |
+
with gr.Column(scale=3):
|
| 976 |
+
gr.Markdown("### 脚本")
|
| 977 |
+
gr.Markdown(
|
| 978 |
+
"脚本可以手工编写也可以从左侧的AI��本生成按钮生成。脚本格式 **角色::文本** 一行为一句” 注意是::")
|
| 979 |
+
script_text = "\n".join(
|
| 980 |
+
[f"{_.get('character', '')}::{_.get('txt', '')}" for _ in script_example['lines']])
|
| 981 |
+
|
| 982 |
+
script_text_input = gr.Textbox(label="脚本格式 “角色::文本 一行为一句” 注意是::",
|
| 983 |
+
placeholder="请输入文本...",
|
| 984 |
+
lines=12, value=script_text)
|
| 985 |
+
script_translate_button = gr.Button("步骤①：提取角色")
|
| 986 |
+
|
| 987 |
+
with gr.Column(scale=1):
|
| 988 |
+
gr.Markdown("### 角色种子")
|
| 989 |
+
# DataFrame 来存放转换后的脚本
|
| 990 |
+
# 默认数据 [speed_5][oral_2][laugh_0][break_4]
|
| 991 |
+
default_data = [
|
| 992 |
+
["旁白", 2222, 3, 0, 0, 2],
|
| 993 |
+
["年轻女性", 2, 5, 2, 0, 2],
|
| 994 |
+
["中年男性", 2424, 5, 2, 0, 2]
|
| 995 |
+
]
|
| 996 |
+
|
| 997 |
+
script_data = gr.DataFrame(
|
| 998 |
+
value=default_data,
|
| 999 |
+
label="角色对应的音色种子，从抽卡那获取",
|
| 1000 |
+
headers=["角色", "种子", "语速", "口语", "笑声", "停顿"],
|
| 1001 |
+
datatype=["str", "number", "number", "number", "number", "number"],
|
| 1002 |
+
interactive=True,
|
| 1003 |
+
col_count=(6, "fixed"),
|
| 1004 |
+
)
|
| 1005 |
+
# 生视频按钮
|
| 1006 |
+
script_generate_audio = gr.Button("步骤②：生成音频")
|
| 1007 |
+
# 输出的脚本音频
|
| 1008 |
+
script_audio = gr.Audio(label="AI生成的音频", interactive=False)
|
| 1009 |
+
|
| 1010 |
+
# 脚本相关事件
|
| 1011 |
+
# 脚本转换
|
| 1012 |
+
script_translate_button.click(
|
| 1013 |
+
get_txt_characters,
|
| 1014 |
+
inputs=[script_text_input],
|
| 1015 |
+
outputs=script_data
|
| 1016 |
+
)
|
| 1017 |
+
# 处理模型切换
|
| 1018 |
+
model_select.change(
|
| 1019 |
+
llm_change,
|
| 1020 |
+
inputs=[model_select],
|
| 1021 |
+
outputs=[openai_api_base_input]
|
| 1022 |
+
)
|
| 1023 |
+
# AI脚本生成
|
| 1024 |
+
ai_script_generate_button.click(
|
| 1025 |
+
ai_script_generate,
|
| 1026 |
+
inputs=[model_select, openai_api_base_input, openai_api_key_input, ai_text_input],
|
| 1027 |
+
outputs=[script_text_input]
|
| 1028 |
+
)
|
| 1029 |
+
# 音频生成
|
| 1030 |
+
script_generate_audio.click(
|
| 1031 |
+
generate_script_audio,
|
| 1032 |
+
inputs=[script_text_input, script_data],
|
| 1033 |
+
outputs=[script_audio]
|
| 1034 |
+
)
|
| 1035 |
+
|
| 1036 |
+
demo.launch(share=args.share, inbrowser=True)
|
zh_normalization/README.md
ADDED
|
@@ -0,0 +1,16 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
## Supported NSW (Non-Standard-Word) Normalization
|
| 2 |
+
|
| 3 |
+
|NSW type|raw|normalized|
|
| 4 |
+
|:--|:-|:-|
|
| 5 |
+
|serial number|电影中梁朝伟扮演的陈永仁的编号27149|电影中梁朝伟扮演的陈永仁的编号二七一四九|
|
| 6 |
+
|cardinal|这块黄金重达324.75克<br>我们班的最高总分为583分|这块黄金重达三百二十四点七五克<br>我们班的最高总分为五百八十三分|
|
| 7 |
+
|numeric range |12\~23<br>-1.5\~2|十二到二十三<br>负一点五到二|
|
| 8 |
+
|date|她出生于86年8月18日，她弟弟出生于1995年3月1日|她出生于八六年八月十八日， 她弟弟出生于一九九五年三月一日|
|
| 9 |
+
|time|等会请在12:05请通知我|等会请在十二点零五分请通知我
|
| 10 |
+
|temperature|今天的最低气温达到-10°C|今天的最低气温达到零下十度
|
| 11 |
+
|fraction|现场有7/12的观众投出了赞成票|现场有十二分之七的观众投出了赞成票|
|
| 12 |
+
|percentage|明天有62％的概率降雨|明天有百分之六十二的概率降雨|
|
| 13 |
+
|money|随便来几个价格12块5，34.5元，20.1万|随便来几个价格十二块五，三十四点五元，二十点一万|
|
| 14 |
+
|telephone|这是固话0421-33441122<br>这是手机+86 18544139121|这是固话零四二一三三四四一一二二<br>这是手机八六一八五四四一三九一二一|
|
| 15 |
+
## References
|
| 16 |
+
[Pull requests #658 of DeepSpeech](https://github.com/PaddlePaddle/DeepSpeech/pull/658/files)
|
zh_normalization/__init__.py
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
|
| 2 |
+
#
|
| 3 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 4 |
+
# you may not use this file except in compliance with the License.
|
| 5 |
+
# You may obtain a copy of the License at
|
| 6 |
+
#
|
| 7 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 8 |
+
#
|
| 9 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 10 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 11 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 12 |
+
# See the License for the specific language governing permissions and
|
| 13 |
+
# limitations under the License.
|
| 14 |
+
from .text_normlization import *
|
zh_normalization/char_convert.py
ADDED
|
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# coding=utf-8
|
| 2 |
+
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
|
| 3 |
+
#
|
| 4 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
+
# you may not use this file except in compliance with the License.
|
| 6 |
+
# You may obtain a copy of the License at
|
| 7 |
+
#
|
| 8 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
+
#
|
| 10 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 11 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
+
# See the License for the specific language governing permissions and
|
| 14 |
+
# limitations under the License.
|
| 15 |
+
"""Traditional and simplified Chinese conversion, a simplified character may correspond to multiple traditional characters.
|
| 16 |
+
"""
|
| 17 |
+
simplified_charcters = 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+
traditional_characters = 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鐃鐄鐇鐏鐒鐓鐔鐗馗鐙鐝鐠鐡鐦鐨鐩鐫鐬鐱鐳鐶鐻鐽鐿鑀鑅鑌鑐鑕鑚鑛鑢鑤鑥鑪鑭鑯鑱鑴鑵鑷钁钃镻閆閈閌閎閒閔閗閟閡関閤閤閧閬閲閹閺閻閼閽閿闇闉闋闐闑闒闓闘闚闞闟闠闤闥阞阢阤阨阬阯阹阼阽陁陑陔陛陜陡陥陬騭陴険陼陾隂隃隈隒隗隞隠隣隤隩隮隰顴隳隷隹雂雈雉雊雎雑雒雗雘雚雝雟雩雰雱驛霂霅霈霊霑霒霓霙霝霢霣霤霨霩霪霫霮靁靆靉靑靚靣靦靪靮靰靳靷靸靺靼靿鞀鞃鞄鞌鞗鞙鞚鞝鞞鞡鞣鞨鞫鞬鞮鞶鞹鞾韃韅韉馱韍韎韔韖韘韝韞韡韣韭韮韱韹韺頀颳頄頇頊頍頎頏頒頖頞頠頫頬顱頯頲頴頼顇顋顑顒顓顔顕顚顜顢顣顬顳颭颮颱颶颸颺颻颽颾颿飀飂飈飌飜飡飣飤飥飩飫飮飱飶餀餂餄餎餇餈餑餔餕餖餗餚餛餜餟餠餤餧餩餪餫餬餮餱餲餳餺餻餼餽餿饁饅饇饉饊饍饎饐饘饟饢馘馥馝馡馣騮騾馵馹駃駄駅駆駉駋駑駓駔駗駘駙駜駡駢駪駬駰駴駸駹駽駾騂騄騅騆騉騋騍騏驎騑騒験騕騖騠騢騣騤騧驤騵騶騸騺驀驂驃驄驆驈驊驌驍驎驏驒驔驖驙驦驩驫骺鯁骫骭骯骱骴骶骷髏骾髁髂髄髆髈髐髑髕髖髙髝髞髟髡髣髧髪髫髭髯髲髳髹髺髽髾鬁鬃鬅鬈鬋鬎鬏鬐鬑鬒鬖鬗鬘鬙鬠鬣鬪鬫鬬鬮鬯鬰鬲鬵鬷魆魈魊魋魍魎魑魖鰾魛魟魣魦魨魬魴魵魸鮀鮁鮆鮌鮎鮑鮒鮓鮚鮞鮟鱇鮠鮦鮨鮪鮭鮶鮸鮿鯀鯄鯆鯇鯈鯔鯕鯖鯗鯙鯠鯤鯥鯫鯰鯷鯸鯿鰂鰆鶼鰉鰋鰐鰒鰕鰛鰜鰣鰤鰥鰦鰨鰩鰮鰳鰶鰷鱺鰼鰽鱀鱄鱅鱆鱈鱎鱐鱓鱔鱖鱘鱟鱠鱣鱨鱭鱮鱲鱵鱻鲅鳦鳧鳯鳲鳷鳻鴂鴃鴄鴆鴈鴎鴒鴔鴗鴛鴦鴝鵒鴟鴠鴢鴣鴥鴯鶓鴳鴴鴷鴽鵀鵁鵂鵓鵖鵙鵜鶘鵞鵟鵩鵪鵫鵵鵷鵻鵾鶂鶊鶏鶒鶖鶗鶡鶤鶦鶬鶱鶲鶵鶸鶹鶺鶿鷀鷁鷃鷄鷇鷈鷉鷊鷏鷓鷕鷖鷙鷞鷟鷥鷦鷯鷩鷫鷭鷳鷴鷽鷾鷿鸂鸇鸊鸏鸑鸒鸓鸕鸛鸜鸝鹸鹹鹺麀麂麃麄麇麋麌麐麑麒麚麛麝麤麩麪麫麮麯麰麺麾黁黈黌黢黒黓黕黙黝黟黥黦黧黮黰黱黲黶黹黻黼黽黿鼂鼃鼅鼈鼉鼏鼐鼒鼕鼖鼙鼚鼛鼡鼩鼱鼪鼫鼯鼷鼽齁齆齇齈齉齌齎齏齔齕齗齙齚齜齞齟齬齠齢齣齧齩齮齯齰齱齵齾龎龑龒龔龖龘龝龡龢龤'
|
| 20 |
+
|
| 21 |
+
assert len(simplified_charcters) == len(simplified_charcters)
|
| 22 |
+
|
| 23 |
+
s2t_dict = {}
|
| 24 |
+
t2s_dict = {}
|
| 25 |
+
for i, item in enumerate(simplified_charcters):
|
| 26 |
+
s2t_dict[item] = traditional_characters[i]
|
| 27 |
+
t2s_dict[traditional_characters[i]] = item
|
| 28 |
+
|
| 29 |
+
|
| 30 |
+
def tranditional_to_simplified(text: str) -> str:
|
| 31 |
+
return "".join(
|
| 32 |
+
[t2s_dict[item] if item in t2s_dict else item for item in text])
|
| 33 |
+
|
| 34 |
+
|
| 35 |
+
def simplified_to_traditional(text: str) -> str:
|
| 36 |
+
return "".join(
|
| 37 |
+
[s2t_dict[item] if item in s2t_dict else item for item in text])
|
| 38 |
+
|
| 39 |
+
|
| 40 |
+
if __name__ == "__main__":
|
| 41 |
+
text = "一般是指存取一個應用程式啟動時始終顯示在網站或網頁瀏覽器中的一個或多個初始網頁等畫面存在的站點"
|
| 42 |
+
print(text)
|
| 43 |
+
text_simple = tranditional_to_simplified(text)
|
| 44 |
+
print(text_simple)
|
| 45 |
+
text_traditional = simplified_to_traditional(text_simple)
|
| 46 |
+
print(text_traditional)
|
zh_normalization/chronology.py
ADDED
|
@@ -0,0 +1,134 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
|
| 2 |
+
#
|
| 3 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 4 |
+
# you may not use this file except in compliance with the License.
|
| 5 |
+
# You may obtain a copy of the License at
|
| 6 |
+
#
|
| 7 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 8 |
+
#
|
| 9 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 10 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 11 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 12 |
+
# See the License for the specific language governing permissions and
|
| 13 |
+
# limitations under the License.
|
| 14 |
+
import re
|
| 15 |
+
|
| 16 |
+
from .num import DIGITS
|
| 17 |
+
from .num import num2str
|
| 18 |
+
from .num import verbalize_cardinal
|
| 19 |
+
from .num import verbalize_digit
|
| 20 |
+
|
| 21 |
+
|
| 22 |
+
def _time_num2str(num_string: str) -> str:
|
| 23 |
+
"""A special case for verbalizing number in time."""
|
| 24 |
+
result = num2str(num_string.lstrip('0'))
|
| 25 |
+
if num_string.startswith('0'):
|
| 26 |
+
result = DIGITS['0'] + result
|
| 27 |
+
return result
|
| 28 |
+
|
| 29 |
+
|
| 30 |
+
# 时刻表达式
|
| 31 |
+
RE_TIME = re.compile(r'([0-1]?[0-9]|2[0-3])'
|
| 32 |
+
r':([0-5][0-9])'
|
| 33 |
+
r'(:([0-5][0-9]))?')
|
| 34 |
+
|
| 35 |
+
# 时间范围，如8:30-12:30
|
| 36 |
+
RE_TIME_RANGE = re.compile(r'([0-1]?[0-9]|2[0-3])'
|
| 37 |
+
r':([0-5][0-9])'
|
| 38 |
+
r'(:([0-5][0-9]))?'
|
| 39 |
+
r'(~|-)'
|
| 40 |
+
r'([0-1]?[0-9]|2[0-3])'
|
| 41 |
+
r':([0-5][0-9])'
|
| 42 |
+
r'(:([0-5][0-9]))?')
|
| 43 |
+
|
| 44 |
+
|
| 45 |
+
def replace_time(match) -> str:
|
| 46 |
+
"""
|
| 47 |
+
Args:
|
| 48 |
+
match (re.Match)
|
| 49 |
+
Returns:
|
| 50 |
+
str
|
| 51 |
+
"""
|
| 52 |
+
|
| 53 |
+
is_range = len(match.groups()) > 5
|
| 54 |
+
|
| 55 |
+
hour = match.group(1)
|
| 56 |
+
minute = match.group(2)
|
| 57 |
+
second = match.group(4)
|
| 58 |
+
|
| 59 |
+
if is_range:
|
| 60 |
+
hour_2 = match.group(6)
|
| 61 |
+
minute_2 = match.group(7)
|
| 62 |
+
second_2 = match.group(9)
|
| 63 |
+
|
| 64 |
+
result = f"{num2str(hour)}点"
|
| 65 |
+
if minute.lstrip('0'):
|
| 66 |
+
if int(minute) == 30:
|
| 67 |
+
result += "半"
|
| 68 |
+
else:
|
| 69 |
+
result += f"{_time_num2str(minute)}分"
|
| 70 |
+
if second and second.lstrip('0'):
|
| 71 |
+
result += f"{_time_num2str(second)}秒"
|
| 72 |
+
|
| 73 |
+
if is_range:
|
| 74 |
+
result += "至"
|
| 75 |
+
result += f"{num2str(hour_2)}点"
|
| 76 |
+
if minute_2.lstrip('0'):
|
| 77 |
+
if int(minute) == 30:
|
| 78 |
+
result += "半"
|
| 79 |
+
else:
|
| 80 |
+
result += f"{_time_num2str(minute_2)}分"
|
| 81 |
+
if second_2 and second_2.lstrip('0'):
|
| 82 |
+
result += f"{_time_num2str(second_2)}秒"
|
| 83 |
+
|
| 84 |
+
return result
|
| 85 |
+
|
| 86 |
+
|
| 87 |
+
RE_DATE = re.compile(r'(\d{4}|\d{2})年'
|
| 88 |
+
r'((0?[1-9]|1[0-2])月)?'
|
| 89 |
+
r'(((0?[1-9])|((1|2)[0-9])|30|31)([日号]))?')
|
| 90 |
+
|
| 91 |
+
|
| 92 |
+
def replace_date(match) -> str:
|
| 93 |
+
"""
|
| 94 |
+
Args:
|
| 95 |
+
match (re.Match)
|
| 96 |
+
Returns:
|
| 97 |
+
str
|
| 98 |
+
"""
|
| 99 |
+
year = match.group(1)
|
| 100 |
+
month = match.group(3)
|
| 101 |
+
day = match.group(5)
|
| 102 |
+
result = ""
|
| 103 |
+
if year:
|
| 104 |
+
result += f"{verbalize_digit(year)}年"
|
| 105 |
+
if month:
|
| 106 |
+
result += f"{verbalize_cardinal(month)}月"
|
| 107 |
+
if day:
|
| 108 |
+
result += f"{verbalize_cardinal(day)}{match.group(9)}"
|
| 109 |
+
return result
|
| 110 |
+
|
| 111 |
+
|
| 112 |
+
# 用 / 或者 - 分隔的 YY/MM/DD 或者 YY-MM-DD 日期
|
| 113 |
+
RE_DATE2 = re.compile(
|
| 114 |
+
r'(\d{4})([- /.])(0[1-9]|1[012])\2(0[1-9]|[12][0-9]|3[01])')
|
| 115 |
+
|
| 116 |
+
|
| 117 |
+
def replace_date2(match) -> str:
|
| 118 |
+
"""
|
| 119 |
+
Args:
|
| 120 |
+
match (re.Match)
|
| 121 |
+
Returns:
|
| 122 |
+
str
|
| 123 |
+
"""
|
| 124 |
+
year = match.group(1)
|
| 125 |
+
month = match.group(3)
|
| 126 |
+
day = match.group(4)
|
| 127 |
+
result = ""
|
| 128 |
+
if year:
|
| 129 |
+
result += f"{verbalize_digit(year)}年"
|
| 130 |
+
if month:
|
| 131 |
+
result += f"{verbalize_cardinal(month)}月"
|
| 132 |
+
if day:
|
| 133 |
+
result += f"{verbalize_cardinal(day)}日"
|
| 134 |
+
return result
|
zh_normalization/constants.py
ADDED
|
@@ -0,0 +1,62 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
|
| 2 |
+
#
|
| 3 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 4 |
+
# you may not use this file except in compliance with the License.
|
| 5 |
+
# You may obtain a copy of the License at
|
| 6 |
+
#
|
| 7 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 8 |
+
#
|
| 9 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 10 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 11 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 12 |
+
# See the License for the specific language governing permissions and
|
| 13 |
+
# limitations under the License.
|
| 14 |
+
import re
|
| 15 |
+
import string
|
| 16 |
+
|
| 17 |
+
from pypinyin.constants import SUPPORT_UCS4
|
| 18 |
+
|
| 19 |
+
# 全角半角转换
|
| 20 |
+
# 英文字符全角 -> 半角映射表 (num: 52)
|
| 21 |
+
F2H_ASCII_LETTERS = {
|
| 22 |
+
ord(char) + 65248: ord(char)
|
| 23 |
+
for char in string.ascii_letters
|
| 24 |
+
}
|
| 25 |
+
|
| 26 |
+
# 英文字符半角 -> 全角映射表
|
| 27 |
+
H2F_ASCII_LETTERS = {value: key for key, value in F2H_ASCII_LETTERS.items()}
|
| 28 |
+
|
| 29 |
+
# 数字字符全角 -> 半角映射表 (num: 10)
|
| 30 |
+
F2H_DIGITS = {ord(char) + 65248: ord(char) for char in string.digits}
|
| 31 |
+
# 数字字符半角 -> 全角映射表
|
| 32 |
+
H2F_DIGITS = {value: key for key, value in F2H_DIGITS.items()}
|
| 33 |
+
|
| 34 |
+
# 标点符号全角 -> 半角映射表 (num: 32)
|
| 35 |
+
F2H_PUNCTUATIONS = {ord(char) + 65248: ord(char) for char in string.punctuation}
|
| 36 |
+
# 标点符号半角 -> 全角映射表
|
| 37 |
+
H2F_PUNCTUATIONS = {value: key for key, value in F2H_PUNCTUATIONS.items()}
|
| 38 |
+
|
| 39 |
+
# 空格 (num: 1)
|
| 40 |
+
F2H_SPACE = {'\u3000': ' '}
|
| 41 |
+
H2F_SPACE = {' ': '\u3000'}
|
| 42 |
+
|
| 43 |
+
# 非"有拼音的汉字"的字符串，可用于NSW提取
|
| 44 |
+
if SUPPORT_UCS4:
|
| 45 |
+
RE_NSW = re.compile(r'(?:[^'
|
| 46 |
+
r'\u3007' # 〇
|
| 47 |
+
r'\u3400-\u4dbf' # CJK扩展A:[3400-4DBF]
|
| 48 |
+
r'\u4e00-\u9fff' # CJK基本:[4E00-9FFF]
|
| 49 |
+
r'\uf900-\ufaff' # CJK兼容:[F900-FAFF]
|
| 50 |
+
r'\U00020000-\U0002A6DF' # CJK扩展B:[20000-2A6DF]
|
| 51 |
+
r'\U0002A703-\U0002B73F' # CJK扩展C:[2A700-2B73F]
|
| 52 |
+
r'\U0002B740-\U0002B81D' # CJK扩展D:[2B740-2B81D]
|
| 53 |
+
r'\U0002F80A-\U0002FA1F' # CJK兼容扩展:[2F800-2FA1F]
|
| 54 |
+
r'])+')
|
| 55 |
+
else:
|
| 56 |
+
RE_NSW = re.compile( # pragma: no cover
|
| 57 |
+
r'(?:[^'
|
| 58 |
+
r'\u3007' # 〇
|
| 59 |
+
r'\u3400-\u4dbf' # CJK扩展A:[3400-4DBF]
|
| 60 |
+
r'\u4e00-\u9fff' # CJK基本:[4E00-9FFF]
|
| 61 |
+
r'\uf900-\ufaff' # CJK兼容:[F900-FAFF]
|
| 62 |
+
r'])+')
|
zh_normalization/num.py
ADDED
|
@@ -0,0 +1,238 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
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|
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|
|
|
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|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
|
| 2 |
+
#
|
| 3 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 4 |
+
# you may not use this file except in compliance with the License.
|
| 5 |
+
# You may obtain a copy of the License at
|
| 6 |
+
#
|
| 7 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 8 |
+
#
|
| 9 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 10 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 11 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 12 |
+
# See the License for the specific language governing permissions and
|
| 13 |
+
# limitations under the License.
|
| 14 |
+
"""
|
| 15 |
+
Rules to verbalize numbers into Chinese characters.
|
| 16 |
+
https://zh.wikipedia.org/wiki/中文数字#現代中文
|
| 17 |
+
"""
|
| 18 |
+
import re
|
| 19 |
+
from collections import OrderedDict
|
| 20 |
+
from typing import List
|
| 21 |
+
|
| 22 |
+
DIGITS = {str(i): tran for i, tran in enumerate('零一二三四五六七八九')}
|
| 23 |
+
UNITS = OrderedDict({
|
| 24 |
+
1: '十',
|
| 25 |
+
2: '百',
|
| 26 |
+
3: '千',
|
| 27 |
+
4: '万',
|
| 28 |
+
8: '亿',
|
| 29 |
+
})
|
| 30 |
+
|
| 31 |
+
COM_QUANTIFIERS = '(封|艘|把|目|套|段|人|所|朵|匹|张|座|回|场|尾|条|个|首|阙|阵|网|炮|顶|丘|棵|只|支|袭|辆|挑|担|颗|壳|窠|曲|墙|群|腔|砣|座|客|贯|扎|捆|刀|令|打|手|罗|坡|山|岭|江|溪|钟|队|单|双|对|出|口|头|脚|板|跳|枝|件|贴|针|线|管|名|位|身|堂|课|本|页|家|户|层|丝|毫|厘|分|钱|两|斤|担|铢|石|钧|锱|忽|(千|毫|微)克|毫|厘|(公)分|分|寸|尺|丈|里|寻|常|铺|程|(千|分|厘|毫|微)米|米|撮|勺|合|升|斗|石|盘|碗|碟|叠|桶|笼|盆|盒|杯|钟|斛|锅|簋|篮|盘|桶|罐|瓶|壶|卮|盏|箩|箱|煲|啖|袋|钵|年|月|日|季|刻|时|周|天|秒|分|小时|旬|纪|岁|世|更|夜|春|夏|秋|冬|代|伏|辈|丸|泡|粒|颗|幢|堆|条|根|支|道|面|片|张|颗|块|元|(亿|千万|百万|万|千|百)|(亿|千万|百万|万|千|百|美|)元|(亿|千万|百万|万|千|百|十|)吨|(亿|千万|百万|万|千|百|)块|角|毛|分)'
|
| 32 |
+
|
| 33 |
+
# 分数表达式
|
| 34 |
+
RE_FRAC = re.compile(r'(-?)(\d+)/(\d+)')
|
| 35 |
+
|
| 36 |
+
|
| 37 |
+
def replace_frac(match) -> str:
|
| 38 |
+
"""
|
| 39 |
+
Args:
|
| 40 |
+
match (re.Match)
|
| 41 |
+
Returns:
|
| 42 |
+
str
|
| 43 |
+
"""
|
| 44 |
+
sign = match.group(1)
|
| 45 |
+
nominator = match.group(2)
|
| 46 |
+
denominator = match.group(3)
|
| 47 |
+
sign: str = "负" if sign else ""
|
| 48 |
+
nominator: str = num2str(nominator)
|
| 49 |
+
denominator: str = num2str(denominator)
|
| 50 |
+
result = f"{sign}{denominator}分之{nominator}"
|
| 51 |
+
return result
|
| 52 |
+
|
| 53 |
+
|
| 54 |
+
# 百分数表达式
|
| 55 |
+
RE_PERCENTAGE = re.compile(r'(-?)(\d+(\.\d+)?)%')
|
| 56 |
+
|
| 57 |
+
|
| 58 |
+
def replace_percentage(match) -> str:
|
| 59 |
+
"""
|
| 60 |
+
Args:
|
| 61 |
+
match (re.Match)
|
| 62 |
+
Returns:
|
| 63 |
+
str
|
| 64 |
+
"""
|
| 65 |
+
sign = match.group(1)
|
| 66 |
+
percent = match.group(2)
|
| 67 |
+
sign: str = "负" if sign else ""
|
| 68 |
+
percent: str = num2str(percent)
|
| 69 |
+
result = f"{sign}百分之{percent}"
|
| 70 |
+
return result
|
| 71 |
+
|
| 72 |
+
|
| 73 |
+
# 整数表达式
|
| 74 |
+
# 带负号的整数 -10
|
| 75 |
+
RE_INTEGER = re.compile(r'(-)' r'(\d+)')
|
| 76 |
+
|
| 77 |
+
|
| 78 |
+
def replace_negative_num(match) -> str:
|
| 79 |
+
"""
|
| 80 |
+
Args:
|
| 81 |
+
match (re.Match)
|
| 82 |
+
Returns:
|
| 83 |
+
str
|
| 84 |
+
"""
|
| 85 |
+
sign = match.group(1)
|
| 86 |
+
number = match.group(2)
|
| 87 |
+
sign: str = "负" if sign else ""
|
| 88 |
+
number: str = num2str(number)
|
| 89 |
+
result = f"{sign}{number}"
|
| 90 |
+
return result
|
| 91 |
+
|
| 92 |
+
|
| 93 |
+
# 编号-无符号整形
|
| 94 |
+
# 00078
|
| 95 |
+
RE_DEFAULT_NUM = re.compile(r'\d{3}\d*')
|
| 96 |
+
|
| 97 |
+
|
| 98 |
+
def replace_default_num(match):
|
| 99 |
+
"""
|
| 100 |
+
Args:
|
| 101 |
+
match (re.Match)
|
| 102 |
+
Returns:
|
| 103 |
+
str
|
| 104 |
+
"""
|
| 105 |
+
number = match.group(0)
|
| 106 |
+
return verbalize_digit(number, alt_one=True)
|
| 107 |
+
|
| 108 |
+
|
| 109 |
+
# 数字表达式
|
| 110 |
+
# 纯小数
|
| 111 |
+
RE_DECIMAL_NUM = re.compile(r'(-?)((\d+)(\.\d+))' r'|(\.(\d+))')
|
| 112 |
+
# 正整数 + 量词
|
| 113 |
+
RE_POSITIVE_QUANTIFIERS = re.compile(r"(\d+)([多余几\+])?" + COM_QUANTIFIERS)
|
| 114 |
+
RE_NUMBER = re.compile(r'(-?)((\d+)(\.\d+)?)' r'|(\.(\d+))')
|
| 115 |
+
|
| 116 |
+
|
| 117 |
+
def replace_positive_quantifier(match) -> str:
|
| 118 |
+
"""
|
| 119 |
+
Args:
|
| 120 |
+
match (re.Match)
|
| 121 |
+
Returns:
|
| 122 |
+
str
|
| 123 |
+
"""
|
| 124 |
+
number = match.group(1)
|
| 125 |
+
match_2 = match.group(2)
|
| 126 |
+
if match_2 == "+":
|
| 127 |
+
match_2 = "多"
|
| 128 |
+
match_2: str = match_2 if match_2 else ""
|
| 129 |
+
quantifiers: str = match.group(3)
|
| 130 |
+
number: str = num2str(number)
|
| 131 |
+
result = f"{number}{match_2}{quantifiers}"
|
| 132 |
+
return result
|
| 133 |
+
|
| 134 |
+
|
| 135 |
+
def replace_number(match) -> str:
|
| 136 |
+
"""
|
| 137 |
+
Args:
|
| 138 |
+
match (re.Match)
|
| 139 |
+
Returns:
|
| 140 |
+
str
|
| 141 |
+
"""
|
| 142 |
+
sign = match.group(1)
|
| 143 |
+
number = match.group(2)
|
| 144 |
+
pure_decimal = match.group(5)
|
| 145 |
+
if pure_decimal:
|
| 146 |
+
result = num2str(pure_decimal)
|
| 147 |
+
else:
|
| 148 |
+
sign: str = "负" if sign else ""
|
| 149 |
+
number: str = num2str(number)
|
| 150 |
+
result = f"{sign}{number}"
|
| 151 |
+
return result
|
| 152 |
+
|
| 153 |
+
|
| 154 |
+
# 范围表达式
|
| 155 |
+
# match.group(1) and match.group(8) are copy from RE_NUMBER
|
| 156 |
+
|
| 157 |
+
RE_RANGE = re.compile(
|
| 158 |
+
r'((-?)((\d+)(\.\d+)?)|(\.(\d+)))[-~]((-?)((\d+)(\.\d+)?)|(\.(\d+)))')
|
| 159 |
+
|
| 160 |
+
|
| 161 |
+
def replace_range(match) -> str:
|
| 162 |
+
"""
|
| 163 |
+
Args:
|
| 164 |
+
match (re.Match)
|
| 165 |
+
Returns:
|
| 166 |
+
str
|
| 167 |
+
"""
|
| 168 |
+
first, second = match.group(1), match.group(8)
|
| 169 |
+
first = RE_NUMBER.sub(replace_number, first)
|
| 170 |
+
second = RE_NUMBER.sub(replace_number, second)
|
| 171 |
+
result = f"{first}到{second}"
|
| 172 |
+
return result
|
| 173 |
+
|
| 174 |
+
|
| 175 |
+
def _get_value(value_string: str, use_zero: bool=True) -> List[str]:
|
| 176 |
+
stripped = value_string.lstrip('0')
|
| 177 |
+
if len(stripped) == 0:
|
| 178 |
+
return []
|
| 179 |
+
elif len(stripped) == 1:
|
| 180 |
+
if use_zero and len(stripped) < len(value_string):
|
| 181 |
+
return [DIGITS['0'], DIGITS[stripped]]
|
| 182 |
+
else:
|
| 183 |
+
return [DIGITS[stripped]]
|
| 184 |
+
else:
|
| 185 |
+
largest_unit = next(
|
| 186 |
+
power for power in reversed(UNITS.keys()) if power < len(stripped))
|
| 187 |
+
first_part = value_string[:-largest_unit]
|
| 188 |
+
second_part = value_string[-largest_unit:]
|
| 189 |
+
return _get_value(first_part) + [UNITS[largest_unit]] + _get_value(
|
| 190 |
+
second_part)
|
| 191 |
+
|
| 192 |
+
|
| 193 |
+
def verbalize_cardinal(value_string: str) -> str:
|
| 194 |
+
if not value_string:
|
| 195 |
+
return ''
|
| 196 |
+
|
| 197 |
+
# 000 -> '零' , 0 -> '零'
|
| 198 |
+
value_string = value_string.lstrip('0')
|
| 199 |
+
if len(value_string) == 0:
|
| 200 |
+
return DIGITS['0']
|
| 201 |
+
|
| 202 |
+
result_symbols = _get_value(value_string)
|
| 203 |
+
# verbalized number starting with '一十*' is abbreviated as `十*`
|
| 204 |
+
if len(result_symbols) >= 2 and result_symbols[0] == DIGITS[
|
| 205 |
+
'1'] and result_symbols[1] == UNITS[1]:
|
| 206 |
+
result_symbols = result_symbols[1:]
|
| 207 |
+
return ''.join(result_symbols)
|
| 208 |
+
|
| 209 |
+
|
| 210 |
+
def verbalize_digit(value_string: str, alt_one=False) -> str:
|
| 211 |
+
result_symbols = [DIGITS[digit] for digit in value_string]
|
| 212 |
+
result = ''.join(result_symbols)
|
| 213 |
+
if alt_one:
|
| 214 |
+
result = result.replace("一", "幺")
|
| 215 |
+
return result
|
| 216 |
+
|
| 217 |
+
|
| 218 |
+
def num2str(value_string: str) -> str:
|
| 219 |
+
integer_decimal = value_string.split('.')
|
| 220 |
+
if len(integer_decimal) == 1:
|
| 221 |
+
integer = integer_decimal[0]
|
| 222 |
+
decimal = ''
|
| 223 |
+
elif len(integer_decimal) == 2:
|
| 224 |
+
integer, decimal = integer_decimal
|
| 225 |
+
else:
|
| 226 |
+
raise ValueError(
|
| 227 |
+
f"The value string: '${value_string}' has more than one point in it."
|
| 228 |
+
)
|
| 229 |
+
|
| 230 |
+
result = verbalize_cardinal(integer)
|
| 231 |
+
|
| 232 |
+
decimal = decimal.rstrip('0')
|
| 233 |
+
if decimal:
|
| 234 |
+
# '.22' is verbalized as '零点二二'
|
| 235 |
+
# '3.20' is verbalized as '三点二
|
| 236 |
+
result = result if result else "零"
|
| 237 |
+
result += '点' + verbalize_digit(decimal)
|
| 238 |
+
return result
|
zh_normalization/phonecode.py
ADDED
|
@@ -0,0 +1,63 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
|
| 2 |
+
#
|
| 3 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 4 |
+
# you may not use this file except in compliance with the License.
|
| 5 |
+
# You may obtain a copy of the License at
|
| 6 |
+
#
|
| 7 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 8 |
+
#
|
| 9 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 10 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 11 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 12 |
+
# See the License for the specific language governing permissions and
|
| 13 |
+
# limitations under the License.
|
| 14 |
+
import re
|
| 15 |
+
|
| 16 |
+
from .num import verbalize_digit
|
| 17 |
+
|
| 18 |
+
# 规范化固话/手机号码
|
| 19 |
+
# 手机
|
| 20 |
+
# http://www.jihaoba.com/news/show/13680
|
| 21 |
+
# 移动：139、138、137、136、135、134、159、158、157、150、151、152、188、187、182、183、184、178、198
|
| 22 |
+
# 联通：130、131、132、156、155、186、185、176
|
| 23 |
+
# 电信：133、153、189、180、181、177
|
| 24 |
+
RE_MOBILE_PHONE = re.compile(
|
| 25 |
+
r"(?<!\d)((\+?86 ?)?1([38]\d|5[0-35-9]|7[678]|9[89])\d{8})(?!\d)")
|
| 26 |
+
RE_TELEPHONE = re.compile(
|
| 27 |
+
r"(?<!\d)((0(10|2[1-3]|[3-9]\d{2})-?)?[1-9]\d{7,8})(?!\d)")
|
| 28 |
+
|
| 29 |
+
# 全国统一的号码400开头
|
| 30 |
+
RE_NATIONAL_UNIFORM_NUMBER = re.compile(r"(400)(-)?\d{3}(-)?\d{4}")
|
| 31 |
+
|
| 32 |
+
|
| 33 |
+
def phone2str(phone_string: str, mobile=True) -> str:
|
| 34 |
+
if mobile:
|
| 35 |
+
sp_parts = phone_string.strip('+').split()
|
| 36 |
+
result = '，'.join(
|
| 37 |
+
[verbalize_digit(part, alt_one=True) for part in sp_parts])
|
| 38 |
+
return result
|
| 39 |
+
else:
|
| 40 |
+
sil_parts = phone_string.split('-')
|
| 41 |
+
result = '，'.join(
|
| 42 |
+
[verbalize_digit(part, alt_one=True) for part in sil_parts])
|
| 43 |
+
return result
|
| 44 |
+
|
| 45 |
+
|
| 46 |
+
def replace_phone(match) -> str:
|
| 47 |
+
"""
|
| 48 |
+
Args:
|
| 49 |
+
match (re.Match)
|
| 50 |
+
Returns:
|
| 51 |
+
str
|
| 52 |
+
"""
|
| 53 |
+
return phone2str(match.group(0), mobile=False)
|
| 54 |
+
|
| 55 |
+
|
| 56 |
+
def replace_mobile(match) -> str:
|
| 57 |
+
"""
|
| 58 |
+
Args:
|
| 59 |
+
match (re.Match)
|
| 60 |
+
Returns:
|
| 61 |
+
str
|
| 62 |
+
"""
|
| 63 |
+
return phone2str(match.group(0))
|
zh_normalization/quantifier.py
ADDED
|
@@ -0,0 +1,63 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
|
| 2 |
+
#
|
| 3 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 4 |
+
# you may not use this file except in compliance with the License.
|
| 5 |
+
# You may obtain a copy of the License at
|
| 6 |
+
#
|
| 7 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 8 |
+
#
|
| 9 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 10 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 11 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 12 |
+
# See the License for the specific language governing permissions and
|
| 13 |
+
# limitations under the License.
|
| 14 |
+
import re
|
| 15 |
+
|
| 16 |
+
from .num import num2str
|
| 17 |
+
|
| 18 |
+
# 温度表达式，温度会影响负号的读法
|
| 19 |
+
# -3°C 零下三度
|
| 20 |
+
RE_TEMPERATURE = re.compile(r'(-?)(\d+(\.\d+)?)(°C|℃|度|摄氏度)')
|
| 21 |
+
measure_dict = {
|
| 22 |
+
"cm2": "平方厘米",
|
| 23 |
+
"cm²": "平方厘米",
|
| 24 |
+
"cm3": "立方厘米",
|
| 25 |
+
"cm³": "立方厘米",
|
| 26 |
+
"cm": "厘米",
|
| 27 |
+
"db": "分贝",
|
| 28 |
+
"ds": "毫秒",
|
| 29 |
+
"kg": "千克",
|
| 30 |
+
"km": "千米",
|
| 31 |
+
"m2": "平方米",
|
| 32 |
+
"m²": "平方米",
|
| 33 |
+
"m³": "立方米",
|
| 34 |
+
"m3": "立方米",
|
| 35 |
+
"ml": "毫升",
|
| 36 |
+
"m": "米",
|
| 37 |
+
"mm": "毫米",
|
| 38 |
+
"s": "秒"
|
| 39 |
+
}
|
| 40 |
+
|
| 41 |
+
|
| 42 |
+
def replace_temperature(match) -> str:
|
| 43 |
+
"""
|
| 44 |
+
Args:
|
| 45 |
+
match (re.Match)
|
| 46 |
+
Returns:
|
| 47 |
+
str
|
| 48 |
+
"""
|
| 49 |
+
sign = match.group(1)
|
| 50 |
+
temperature = match.group(2)
|
| 51 |
+
unit = match.group(3)
|
| 52 |
+
sign: str = "零下" if sign else ""
|
| 53 |
+
temperature: str = num2str(temperature)
|
| 54 |
+
unit: str = "摄氏度" if unit == "摄氏度" else "度"
|
| 55 |
+
result = f"{sign}{temperature}{unit}"
|
| 56 |
+
return result
|
| 57 |
+
|
| 58 |
+
|
| 59 |
+
def replace_measure(sentence) -> str:
|
| 60 |
+
for q_notation in measure_dict:
|
| 61 |
+
if q_notation in sentence:
|
| 62 |
+
sentence = sentence.replace(q_notation, measure_dict[q_notation])
|
| 63 |
+
return sentence
|
zh_normalization/text_normlization.py
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
|
| 2 |
+
#
|
| 3 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 4 |
+
# you may not use this file except in compliance with the License.
|
| 5 |
+
# You may obtain a copy of the License at
|
| 6 |
+
#
|
| 7 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 8 |
+
#
|
| 9 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 10 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 11 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 12 |
+
# See the License for the specific language governing permissions and
|
| 13 |
+
# limitations under the License.
|
| 14 |
+
import re
|
| 15 |
+
from typing import List
|
| 16 |
+
|
| 17 |
+
from .char_convert import tranditional_to_simplified
|
| 18 |
+
from .chronology import RE_DATE
|
| 19 |
+
from .chronology import RE_DATE2
|
| 20 |
+
from .chronology import RE_TIME
|
| 21 |
+
from .chronology import RE_TIME_RANGE
|
| 22 |
+
from .chronology import replace_date
|
| 23 |
+
from .chronology import replace_date2
|
| 24 |
+
from .chronology import replace_time
|
| 25 |
+
from .constants import F2H_ASCII_LETTERS
|
| 26 |
+
from .constants import F2H_DIGITS
|
| 27 |
+
from .constants import F2H_SPACE
|
| 28 |
+
from .num import RE_DECIMAL_NUM
|
| 29 |
+
from .num import RE_DEFAULT_NUM
|
| 30 |
+
from .num import RE_FRAC
|
| 31 |
+
from .num import RE_INTEGER
|
| 32 |
+
from .num import RE_NUMBER
|
| 33 |
+
from .num import RE_PERCENTAGE
|
| 34 |
+
from .num import RE_POSITIVE_QUANTIFIERS
|
| 35 |
+
from .num import RE_RANGE
|
| 36 |
+
from .num import replace_default_num
|
| 37 |
+
from .num import replace_frac
|
| 38 |
+
from .num import replace_negative_num
|
| 39 |
+
from .num import replace_number
|
| 40 |
+
from .num import replace_percentage
|
| 41 |
+
from .num import replace_positive_quantifier
|
| 42 |
+
from .num import replace_range
|
| 43 |
+
from .phonecode import RE_MOBILE_PHONE
|
| 44 |
+
from .phonecode import RE_NATIONAL_UNIFORM_NUMBER
|
| 45 |
+
from .phonecode import RE_TELEPHONE
|
| 46 |
+
from .phonecode import replace_mobile
|
| 47 |
+
from .phonecode import replace_phone
|
| 48 |
+
from .quantifier import RE_TEMPERATURE
|
| 49 |
+
from .quantifier import replace_measure
|
| 50 |
+
from .quantifier import replace_temperature
|
| 51 |
+
|
| 52 |
+
|
| 53 |
+
class TextNormalizer():
|
| 54 |
+
def __init__(self):
|
| 55 |
+
self.SENTENCE_SPLITOR = re.compile(r'([：、，；。？！,;?!][”’]?)')
|
| 56 |
+
|
| 57 |
+
def _split(self, text: str, lang="zh") -> List[str]:
|
| 58 |
+
"""Split long text into sentences with sentence-splitting punctuations.
|
| 59 |
+
Args:
|
| 60 |
+
text (str): The input text.
|
| 61 |
+
Returns:
|
| 62 |
+
List[str]: Sentences.
|
| 63 |
+
"""
|
| 64 |
+
# Only for pure Chinese here
|
| 65 |
+
if lang == "zh":
|
| 66 |
+
text = text.replace(" ", "")
|
| 67 |
+
# 过滤掉特殊字符
|
| 68 |
+
text = re.sub(r'[——《》【】<=>{}()（）#&@“”^_|…\\]', '', text)
|
| 69 |
+
text = self.SENTENCE_SPLITOR.sub(r'\1\n', text)
|
| 70 |
+
text = text.strip()
|
| 71 |
+
sentences = [sentence.strip() for sentence in re.split(r'\n+', text)]
|
| 72 |
+
return sentences
|
| 73 |
+
|
| 74 |
+
def _post_replace(self, sentence: str) -> str:
|
| 75 |
+
sentence = sentence.replace('/', '每')
|
| 76 |
+
sentence = sentence.replace('~', '至')
|
| 77 |
+
sentence = sentence.replace('～', '至')
|
| 78 |
+
sentence = sentence.replace('①', '一')
|
| 79 |
+
sentence = sentence.replace('②', '二')
|
| 80 |
+
sentence = sentence.replace('③', '三')
|
| 81 |
+
sentence = sentence.replace('④', '四')
|
| 82 |
+
sentence = sentence.replace('⑤', '五')
|
| 83 |
+
sentence = sentence.replace('⑥', '六')
|
| 84 |
+
sentence = sentence.replace('⑦', '七')
|
| 85 |
+
sentence = sentence.replace('⑧', '八')
|
| 86 |
+
sentence = sentence.replace('⑨', '九')
|
| 87 |
+
sentence = sentence.replace('⑩', '十')
|
| 88 |
+
sentence = sentence.replace('α', '阿尔法')
|
| 89 |
+
sentence = sentence.replace('β', '贝塔')
|
| 90 |
+
sentence = sentence.replace('γ', '伽玛').replace('Γ', '伽玛')
|
| 91 |
+
sentence = sentence.replace('δ', '德尔塔').replace('Δ', '德尔塔')
|
| 92 |
+
sentence = sentence.replace('ε', '艾普西龙')
|
| 93 |
+
sentence = sentence.replace('ζ', '捷塔')
|
| 94 |
+
sentence = sentence.replace('η', '依塔')
|
| 95 |
+
sentence = sentence.replace('θ', '西塔').replace('Θ', '西塔')
|
| 96 |
+
sentence = sentence.replace('ι', '艾欧塔')
|
| 97 |
+
sentence = sentence.replace('κ', '喀帕')
|
| 98 |
+
sentence = sentence.replace('λ', '拉姆达').replace('Λ', '拉姆达')
|
| 99 |
+
sentence = sentence.replace('μ', '缪')
|
| 100 |
+
sentence = sentence.replace('ν', '拗')
|
| 101 |
+
sentence = sentence.replace('ξ', '克西').replace('Ξ', '克西')
|
| 102 |
+
sentence = sentence.replace('ο', '欧米克伦')
|
| 103 |
+
sentence = sentence.replace('π', '派').replace('Π', '派')
|
| 104 |
+
sentence = sentence.replace('ρ', '肉')
|
| 105 |
+
sentence = sentence.replace('ς', '西格玛').replace('Σ', '西格玛').replace(
|
| 106 |
+
'σ', '西格玛')
|
| 107 |
+
sentence = sentence.replace('τ', '套')
|
| 108 |
+
sentence = sentence.replace('υ', '宇普西龙')
|
| 109 |
+
sentence = sentence.replace('φ', '服艾').replace('Φ', '服艾')
|
| 110 |
+
sentence = sentence.replace('χ', '器')
|
| 111 |
+
sentence = sentence.replace('ψ', '普赛').replace('Ψ', '普赛')
|
| 112 |
+
sentence = sentence.replace('ω', '欧米伽').replace('Ω', '欧米伽')
|
| 113 |
+
# re filter special characters, have one more character "-" than line 68
|
| 114 |
+
sentence = re.sub(r'[-——《》【】<=>{}()（）#&@“”^_|…\\]', '', sentence)
|
| 115 |
+
return sentence
|
| 116 |
+
|
| 117 |
+
def normalize_sentence(self, sentence: str) -> str:
|
| 118 |
+
# basic character conversions
|
| 119 |
+
sentence = tranditional_to_simplified(sentence)
|
| 120 |
+
sentence = sentence.translate(F2H_ASCII_LETTERS).translate(
|
| 121 |
+
F2H_DIGITS).translate(F2H_SPACE)
|
| 122 |
+
|
| 123 |
+
# number related NSW verbalization
|
| 124 |
+
sentence = RE_DATE.sub(replace_date, sentence)
|
| 125 |
+
sentence = RE_DATE2.sub(replace_date2, sentence)
|
| 126 |
+
|
| 127 |
+
# range first
|
| 128 |
+
sentence = RE_TIME_RANGE.sub(replace_time, sentence)
|
| 129 |
+
sentence = RE_TIME.sub(replace_time, sentence)
|
| 130 |
+
|
| 131 |
+
sentence = RE_TEMPERATURE.sub(replace_temperature, sentence)
|
| 132 |
+
sentence = replace_measure(sentence)
|
| 133 |
+
sentence = RE_FRAC.sub(replace_frac, sentence)
|
| 134 |
+
sentence = RE_PERCENTAGE.sub(replace_percentage, sentence)
|
| 135 |
+
sentence = RE_MOBILE_PHONE.sub(replace_mobile, sentence)
|
| 136 |
+
|
| 137 |
+
sentence = RE_TELEPHONE.sub(replace_phone, sentence)
|
| 138 |
+
sentence = RE_NATIONAL_UNIFORM_NUMBER.sub(replace_phone, sentence)
|
| 139 |
+
|
| 140 |
+
sentence = RE_RANGE.sub(replace_range, sentence)
|
| 141 |
+
sentence = RE_INTEGER.sub(replace_negative_num, sentence)
|
| 142 |
+
sentence = RE_DECIMAL_NUM.sub(replace_number, sentence)
|
| 143 |
+
sentence = RE_POSITIVE_QUANTIFIERS.sub(replace_positive_quantifier,
|
| 144 |
+
sentence)
|
| 145 |
+
sentence = RE_DEFAULT_NUM.sub(replace_default_num, sentence)
|
| 146 |
+
sentence = RE_NUMBER.sub(replace_number, sentence)
|
| 147 |
+
sentence = self._post_replace(sentence)
|
| 148 |
+
|
| 149 |
+
return sentence
|
| 150 |
+
|
| 151 |
+
def normalize(self, text: str) -> List[str]:
|
| 152 |
+
sentences = self._split(text)
|
| 153 |
+
sentences = [self.normalize_sentence(sent) for sent in sentences]
|
| 154 |
+
return sentences
|