
Chenyme-AAVT
这是一个全自动(音频)视频翻译项目。利用Whisper识别声音,AI大模型翻译字幕,最后合并字幕视频,生成翻译后的视频。
Stars: 1189

Chenyme-AAVT is a user-friendly tool that provides automatic video and audio recognition and translation. It leverages the capabilities of Whisper, a powerful speech recognition model, to accurately identify speech in videos and audios. The recognized speech is then translated using ChatGPT or KIMI, ensuring high-quality translations. With Chenyme-AAVT, you can quickly generate字幕 files and merge them with the original video, making video translation a breeze. The tool supports various languages, allowing you to translate videos and audios into your desired language. Additionally, Chenyme-AAVT offers features such as VAD (Voice Activity Detection) to enhance recognition accuracy, GPU acceleration for faster processing, and support for multiple字幕 formats. Whether you're a content creator, translator, or anyone looking to make video translation more efficient, Chenyme-AAVT is an invaluable tool.
README:
[!NOTE] 🌟 如果本项目对您有帮助,记得 Star 🌟 支持一下吧~
📝 推荐识别时使用 Large 模型以获取更好的体验!由于正在备考,更新速度会放缓,感谢理解!
Chenyme-AAVT 全自动视频翻译项目 致力于提供一个简便高效且免费的媒体识别与翻译自动化流程,帮助您快速完成音视频字幕的识别、翻译和处理等多种功能,当然目前项目已经不仅仅是帮您识别并翻译声音,还可以自动化生成营销图文、对字幕单独翻译。计划未来会基于现有基本功能继续加入更多有意思的工具,比如 实时识别、口型校正、声音克隆、音色辨别 等等,敬请期待!
当前已支持的基本功能,非全部功能:
👉 TODO | 待办事项
- [x] 更换更快的Whisper项目
- [x] 支持本地模型加载
- [x] 支持个人微调Whisper模型
- [x] VAD辅助优化
- [x] 字词级断句优化
- [x] 更多的语种识别
- [ ] 音色辨别
- [ ] 实时语音翻译
- [x] 翻译优化
- [x] 更多的语种翻译
- [x] 更多的翻译模型
- [x] 更多的翻译引擎
- [x] 支持本地大语言模型翻译
- [x] 个性化字幕
- [x] 更多字幕格式
- [x] 字幕预览、实时修改
- [ ] 自动化字幕文本校对
- [ ] 双字幕
- [ ] 视频中文配音
- [ ] 声音克隆
- [ ] 口型校对
- [x] 生成图文
- [ ] 更多写作风格
- [ ] 优化生成效率
- [ ] 提高成品率
- [x] AI助手
- [x] 视频预览
- 支持识别和翻译多种语言
- 支持 全流程本地化、免费化部署
- 支持对视频 一键生成博客内容、营销图文
- 支持 自动化翻译、二次修改字幕、预览视频
- 支持开启 GPU 加速、VAD 辅助、FFmpeg 加速
- 支持使用 ChatGPT、Claude、Gemini、DeepSeek 等众多大模型翻译引擎
[!WARNING]
这些 dll 缺失 多个依赖 CUDA 和 Pytorch 的项目均有此问题,希望相关官方尽快修复 ~
以下解决方法经过本人验证可有效解决,麻烦给颗🌟Star吧!
👉 前置环境:Python、FFmpeg、CUDA 说明
Python | 📖 教程
- 💡 选择 Python > 3.8 的版本
- 前往 Python 官网下载 安装程序
- 运行安装,在安装时请点击 ADD TO PATH 选项
FFMpeg | 📖 教程
- 💡 若您不知道如何安装编译,请直接在项目Release中的下载
Win
版本,自带编译后的FFMpeg - 前往 FFMpeg 官网下载编译好的 Windows 版本
- 设置 FFmpeg 为环境变量
CUDA(CPU 可忽略) | 📖 教程
- 💡 推荐使用版本为 CUDA11.8、12.1、12.4
- 前往 CUDA 官网下载 CUDA 安装程序
- 安装 CUDA
‼️ 请确保前置环境已准备好后再继续下面的步骤‼️
- 前往 Release 页面下载
Win
的最新发行版 (Win/Small)- 运行
1_Install.bat
,等待脚本检查- 通过后根据界面内提示选择版本安装
- 运行
2_WebUI.bat
- 输入
chenymeaavt
进入项目(此为新版本的保护功能,可关闭)
ℹ️ WebUI 会自动拉起,若没有自动跳转请手动在浏览器输入
localhost:8501
👉 前置环境:Python、Brew 说明
- 💡 选择 Python > 3.8 的版本
- 前往 Python 官网下载 PGK 安装包
- 运行安装,页面内选择标准安装
- 💡 使用下面的命令进行一键安装安装
brew
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
‼️ 请确保前置环境已准备好后再继续下面的步骤‼️ brew install FFMpeg
- 前往 Release 页面下载
Mac
的最新发行版 (Mac/Small)- cd 到项目根路径
pip3 install -r requirements.txt
streamlit run Chenyme-AAVT.py
- 输入
chenymeaavt
进入项目(此为新版本的保护功能,可关闭)
ℹ️ WebUI 会自动拉起,若没有自动跳转请手动在浏览器输入
localhost:8501
感谢 @dhlsam 提供此版本
具体使用方法,请查阅:📖 issues/36
感谢 @Kirie233 提供此版本
💡 目前 项目最新版本为 V0.9.0 此 Docker 方法的版本为 V0.8.x,
感谢 @Eisaichen 提供此版本
具体使用方法,请查阅:📖 eisai/chenyme-aavt
docker pull eisai/chenyme-aavt
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