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✦ Free & open sourceWriting

pyVideoTrans

Desktop, web and CLI tool that transcribes, translates, dubs and re-muxes a video into another language.

Translate and dub a video in one pass

Speech recognition, subtitle translation, AI voices and video merge in one free desktop app.

Free forever · open source · GPL-3.0
✓ Light setup✓ Browser-based✓ Real-time collaboration
7.8
ZEKAI
Flexible but technical
Free & open source · Writing
Ease of setup5
Usefulness8
Maintenance9.5
Community8.5
★ 19,721
GITHUB
Nov 2026
UPDATED
GPL-3.0
LICENSE
🛠 Don't want to self-host? We can set it up →
⚡ Quick answer

pyVideoTrans runs the whole chain of recognising speech, translating subtitles, synthesising a dub and merging it back into the video. It suits creators and localisers who want to pick their own models and keep the files on their machine.

Runs on
Cross-platform
Hosting
Desktop
Languages
Python
License
GPL-3.0

What it is

You feed it a video and it runs speech recognition, subtitle translation, text-to-speech and video synthesis, with a pause at each stage so you can proofread. It can also work as separate tools for audio-to-SRT, subtitle translation and text-to-speech, and it offers speaker diarization plus voice cloning through models such as F5-TTS, CosyVoice and GPT-SoVITS.

Who it's for

It suits YouTubers, course makers and subtitle teams who want to mix local models with online APIs and edit each stage by hand. It is a poor fit if you want a polished hosted service with support, or if you cannot check the licences of the third-party models you plug in.

Key features

One-click video translation

Chains recognition, subtitle translation, speech synthesis and video merge into one run.

Pause and proofread stages

You can stop and hand-edit the transcript, translation and dub before continuing.

Multi-speaker dubbing

Speaker diarization lets you give each speaker a different AI voice.

Voice cloning models

Plugs into F5-TTS, CosyVoice and GPT-SoVITS for zero-shot voice cloning.

GUI, WebUI and CLI

Use the desktop app, a browser interface on port 7860, or a headless command line.

Vocal separation toolkit

Includes vocal separation, subtitle merging and audio-video alignment helpers.

How to start

Up and running in 3 steps

1
On Windows 10/11, download the pre-packaged build from the GitHub releases page, unzip it to a path without spaces or Chinese characters, and run sp.exe
2
On macOS or Linux, install FFmpeg and uv, then run git clone, uv sync and uv run sp.py
3
Pick a recogniser, translator and voice engine in the settings, drop in a video and run it; use the pause options to proofread each stage
Real talk

Our honest verdict

What's great

  • Ships a pre-packaged Windows .exe, so Windows users skip the Python setup
  • Lets you swap the recogniser, translator and voice engine independently, from local Faster-Whisper and Ollama to online APIs
  • Offers stage-by-stage manual correction instead of a single black-box output
  • Has a CLI and a Docker WebUI for batch or server use

Where it falls short

  • Local recognition and voice cloning want an NVIDIA GPU with CUDA 12.8 and cuDNN 9.11 for decent speed; AMD acceleration goes through a separate Whisper.NET setup
  • macOS and Linux users must install from source with Python 3.10, FFmpeg and uv
  • Paid translation or TTS APIs are billed by their vendors, and each local model has its own licence you must check for commercial use
  • The documentation site and community Q&A are largely Chinese-first
Cost

Pricing & license

Free under GPL-3.0; the project site states there is no subscription, sign-up or licence code. Your only costs are hardware and any paid translation or voice APIs you connect, which are billed by those vendors.

Paid work

Open remote AI-training roles

870 open remote AI-training roles, updated November 14, 2026; most pay $20–$170 an hour. Zekai lists them free; the application goes to the employer’s platform.

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Questions

FAQ

Is pyVideoTrans free for commercial work?

The code is GPL-3.0 and the project site says there are no fees or sign-up. The README adds that integrated local models and online APIs carry their own terms, so check those before commercial use.

Do I need a GPU?

The site says it runs with or without an NVIDIA card. A card with CUDA speeds up local recognition, and the README names CUDA 12.8 and cuDNN 9.11 for that.

Can it run on a server?

Yes. The README documents a CLI for headless runs and a Gradio-based WebUI, with a Docker image exposing port 7860.

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