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ConfigsJul 17, 2026·3 min de lecture

VideoLingo — Netflix-Level Video Subtitle Translation and Dubbing

Open-source automated video translation pipeline that delivers subtitle cutting, translation, alignment, and AI dubbing in one click.

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Installation avec revue préalable

Cet actif nécessite une revue. Le prompt copié demande un dry-run, affiche les écritures, puis continue seulement après confirmation.

Needs Confirmation · 66/100Policy : confirmer
Surface agent
Tout agent MCP/CLI
Type
Skill
Installation
Single
Confiance
Confiance : Established
Point d'entrée
VideoLingo Overview
Commande avec revue préalable
npx -y tokrepo@latest install 820af45f-81fb-11f1-9bc6-00163e2b0d79 --target codex

Dry-run d'abord, confirmez les écritures, puis lancez cette commande.

Introduction

VideoLingo is an open-source, one-click automated video subtitle team that handles the full pipeline from transcription to dubbing. It produces Netflix-quality subtitle cutting, multi-language translation, precise alignment, and optional AI voice dubbing, making professional video localization accessible to individual creators and small teams.

What VideoLingo Does

  • Transcribes audio using Whisper with accurate word-level timestamps
  • Cuts subtitles at natural sentence boundaries rather than fixed time intervals
  • Translates subtitles across dozens of languages with context-aware LLM translation
  • Aligns translated subtitles to match original speech timing precisely
  • Generates AI dubbing in the target language synchronized to the video

Architecture Overview

VideoLingo chains several AI models into a sequential pipeline. Whisper handles speech recognition, an LLM (GPT, Claude, or local models via Ollama) performs context-aware translation, and a TTS engine (Azure, OpenAI, or Fish Speech) generates the dubbed audio. A Streamlit web UI orchestrates the workflow and lets users adjust parameters between steps. The subtitle alignment module uses dynamic programming to match translated text duration to source speech segments.

Self-Hosting & Configuration

  • Clone the repository and install Python dependencies with pip
  • Configure API keys for your preferred LLM and TTS providers in the web UI
  • Supports local models through Ollama for fully offline operation
  • Run via Streamlit for the web interface or use CLI scripts for batch processing
  • Docker deployment available for containerized setups

Key Features

  • Intelligent subtitle segmentation that respects sentence and clause boundaries
  • Multi-step translation with terminology consistency across the entire video
  • Supports 80+ languages for both subtitles and AI dubbing
  • Built-in quality checks that flag timing mismatches and translation issues
  • Batch mode for processing multiple videos in sequence

Comparison with Similar Tools

  • pyvideotrans — similar pipeline but VideoLingo focuses on subtitle quality with smarter segmentation
  • Subtitle Edit — manual subtitle editor; VideoLingo automates the entire flow end-to-end
  • Kapwing — cloud-based with usage limits; VideoLingo is self-hosted and unlimited
  • Rask AI — commercial SaaS for video translation; VideoLingo is free and open source
  • WhisperX — transcription only; VideoLingo adds translation, alignment, and dubbing

FAQ

Q: What languages does VideoLingo support? A: It supports 80+ languages for subtitles and a growing set for AI dubbing depending on your TTS provider.

Q: Can I use VideoLingo without any API keys? A: Yes, by configuring Ollama for translation and a local TTS model, you can run the entire pipeline offline.

Q: How long does it take to process a 10-minute video? A: Processing time depends on your hardware and chosen models, but typically 5-15 minutes for transcription, translation, and subtitle generation on a modern GPU.

Q: Does VideoLingo preserve the original audio when adding dubs? A: Yes, it can mix the dubbed voice track with the original background audio and music.

Sources

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