
VideoLingo
Netflix-level subtitle cutting, translation, alignment, and even dubbing - one-click fully automated AI video subtitle team | Netflix级字幕切割、翻译、对齐、甚至加上配音,一键全自动视频搬运AI字幕组
Stars: 12149

VideoLingo is an all-in-one video translation and localization dubbing tool designed to generate Netflix-level high-quality subtitles. It aims to eliminate stiff machine translation, multiple lines of subtitles, and can even add high-quality dubbing, allowing knowledge from around the world to be shared across language barriers. Through an intuitive Streamlit web interface, the entire process from video link to embedded high-quality bilingual subtitles and even dubbing can be completed with just two clicks, easily creating Netflix-quality localized videos. Key features and functions include using yt-dlp to download videos from Youtube links, using WhisperX for word-level timeline subtitle recognition, using NLP and GPT for subtitle segmentation based on sentence meaning, summarizing intelligent term knowledge base with GPT for context-aware translation, three-step direct translation, reflection, and free translation to eliminate strange machine translation, checking single-line subtitle length and translation quality according to Netflix standards, using GPT-SoVITS for high-quality aligned dubbing, and integrating package for one-click startup and one-click output in streamlit.
README:
🌟 Overview (Try VL Now!)
VideoLingo is an all-in-one video translation, localization, and dubbing tool aimed at generating Netflix-quality subtitles. It eliminates stiff machine translations and multi-line subtitles while adding high-quality dubbing, enabling global knowledge sharing across language barriers.
Key features:
-
🎥 YouTube video download via yt-dlp
-
🎙️ Word-level and Low-illusion subtitle recognition with WhisperX
-
📝 NLP and AI-powered subtitle segmentation
-
📚 Custom + AI-generated terminology for coherent translation
-
🔄 3-step Translate-Reflect-Adaptation for cinematic quality
-
✅ Netflix-standard, Single-line subtitles Only
-
🗣️ Dubbing with GPT-SoVITS, Azure, OpenAI, and more
-
🚀 One-click startup and processing in Streamlit
-
🌍 Multi-language support in Streamlit UI
-
📝 Detailed logging with progress resumption
Difference from similar projects: Single-line subtitles only, superior translation quality, seamless dubbing experience
Input Language Support(more to come):
🇺🇸 English 🤩 | 🇷🇺 Russian 😊 | 🇫🇷 French 🤩 | 🇩🇪 German 🤩 | 🇮🇹 Italian 🤩 | 🇪🇸 Spanish 🤩 | 🇯🇵 Japanese 😐 | 🇨🇳 Chinese* 😊
*Chinese uses a separate punctuation-enhanced whisper model, for now...
Translation supports all languages, while dubbing language depends on the chosen TTS method.
You don't have to read the whole docs, here is an online AI agent to help you.
Note: For Windows users with NVIDIA GPU, follow these steps before installation:
- Install CUDA Toolkit 12.6
- Install CUDNN 9.3.0
- Add
C:\Program Files\NVIDIA\CUDNN\v9.3\bin\12.6
to your system PATH- Restart your computer
Note: FFmpeg is required. Please install it via package managers:
- Windows:
choco install ffmpeg
(via Chocolatey)- macOS:
brew install ffmpeg
(via Homebrew)- Linux:
sudo apt install ffmpeg
(Debian/Ubuntu)
- Clone the repository
git clone https://github.com/Huanshere/VideoLingo.git
cd VideoLingo
- Install dependencies(requires
python=3.10
)
conda create -n videolingo python=3.10.0 -y
conda activate videolingo
python install.py
- Start the application
streamlit run st.py
Alternatively, you can use Docker (requires CUDA 12.4 and NVIDIA Driver version >550), see Docker docs:
docker build -t videolingo .
docker run -d -p 8501:8501 --gpus all videolingo
VideoLingo supports OpenAI-Like API format and various TTS interfaces:
- LLM:
claude-3-5-sonnet-20240620
,deepseek-chat(v3)
,gemini-2.0-flash-exp
,gpt-4o
, ... (sorted by performance) - WhisperX: Run whisperX locally or use 302.ai API
- TTS:
azure-tts
,openai-tts
,siliconflow-fishtts
,fish-tts
,GPT-SoVITS
,edge-tts
,*custom-tts
(You can modify your own TTS in custom_tts.py!)
Note: VideoLingo works with 302.ai - one API key for all services (LLM, WhisperX, TTS). Or run locally with Ollama and Edge-TTS for free, no API needed!
For detailed installation, API configuration, and batch mode instructions, please refer to the documentation: English | 中文
-
WhisperX transcription performance may be affected by video background noise, as it uses wav2vac model for alignment. For videos with loud background music, please enable Voice Separation Enhancement. Additionally, subtitles ending with numbers or special characters may be truncated early due to wav2vac's inability to map numeric characters (e.g., "1") to their spoken form ("one").
-
Using weaker models can lead to errors during intermediate processes due to strict JSON format requirements for responses. If this error occurs, please delete the
output
folder and retry with a different LLM, otherwise repeated execution will read the previous erroneous response causing the same error. -
The dubbing feature may not be 100% perfect due to differences in speech rates and intonation between languages, as well as the impact of the translation step. However, this project has implemented extensive engineering processing for speech rates to ensure the best possible dubbing results.
-
Multilingual video transcription recognition will only retain the main language. This is because whisperX uses a specialized model for a single language when forcibly aligning word-level subtitles, and will delete unrecognized languages.
-
Cannot dub multiple characters separately, as whisperX's speaker distinction capability is not sufficiently reliable.
This project is licensed under the Apache 2.0 License. Special thanks to the following open source projects for their contributions:
whisperX, yt-dlp, json_repair, BELLE
- Submit Issues or Pull Requests on GitHub
- DM me on Twitter: @Huanshere
- Email me at: [email protected]
If you find VideoLingo helpful, please give me a ⭐️!
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