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Connect the World, Frame by Frame

English｜简体中文｜繁體中文｜日本語｜Español｜Русский｜Français

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.

Meet any problem? Chat with our free online AI agenthere to help you.

Note: For Windows users with NVIDIA GPU, follow these steps before installation:

1. InstallCUDA Toolkit 12.6
2. InstallCUDNN 9.3.0
3. AddC:\Program Files\NVIDIA\CUDNN\v9.3\bin\12.6 to your system PATH
4. Restart your computer

Note: FFmpeg is required. Please install it via package managers:

• Windows:choco install ffmpeg (viaChocolatey)
• macOS:brew install ffmpeg (viaHomebrew)
• Linux:sudo apt install ffmpeg (Debian/Ubuntu)

1. Clone the repository

git clone https://github.com/Huanshere/VideoLingo.gitcd VideoLingo

2. Install dependencies(requirespython=3.10)

conda create -n videolingo python=3.10.0 -yconda activate videolingopython install.py

3. Start the application

streamlit run st.py

Alternatively, you can use Docker (requires CUDA 12.4 and NVIDIA Driver version >550), seeDocker 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,gpt-4.1,deepseek-v3,gemini-2.0-flash, ... (sorted by performance, be cautious with gemini-2.5-flash...)
• WhisperX: Run whisperX (large-v3) 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 with302.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

1. 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").

2. Using weaker models can lead to errors during processes due to strict JSON format requirements for responses (tried my best to prompt llm😊). If this error occurs, please delete theoutput folder and retry with a different LLM, otherwise repeated execution will read the previous erroneous response causing the same error.

3. 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.

4. 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.

5. For now, 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

• SubmitIssues orPull Requests on GitHub
• DM me on Twitter:@Huanshere
• Email me at:team@videolingo.io

If you find VideoLingo helpful, please give me a ⭐️!