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Linly-Dubbing

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What Linly-Dubbing is

Linly-Dubbing is an open-source tool for translating and dubbing videos into multiple languages. Its documented workflow includes AI speech-to-text and speaker recognition, with WhisperX and FunASR named in the project documentation. For translation, it describes OpenAI models, locally run Qwen, and Google Translate. Speech synthesis options include Edge TTS, XTTS, CosyVoice, and GPT-SoVITS; voice cloning can generate speech resembling the voice in the original video. Linly-Talker digital-human lip-sync technology synchronizes dubbed speech with video visuals. The video tools can add subtitles and background music, adjust music volume, and change playback speed. Vocal separation options include Demucs and UVR5. The documentation also describes automatic downloads through yt-dlp, including YouTube and other websites. Linly-Dubbing supports Windows and Linux, with instructions for a local WebUI and an online experience through a linked Colab script. Setup instructions use Python 3.10, PyTorch 2.3.1, and CUDA 11.8 or 12.1. Depending on configuration, setup may require Hugging Face or service credentials. The repository identifies the project as Apache License 2.0, and its releases page currently states there are no releases. The project advises users to comply with copyright, data protection, and privacy laws and obtain permission from rights holders.

Who it suits

Linly-Dubbing suits people who want to translate and dub videos using speech recognition, translation, voice synthesis, and lip synchronization. It may fit users prepared to follow the Windows or Linux setup instructions and configure any credentials their chosen services require.

What it does well

  • Supports speech-to-text and speaker recognition.
  • Offers several documented translation and speech synthesis options.
  • Voice cloning can resemble the original video's voice.
  • Lip-sync technology aligns dubbed speech with video visuals.
  • Includes subtitles, music controls, playback speed, and vocal separation.

What to know first

  • Setup instructions use Python 3.10, PyTorch 2.3.1, and CUDA.
  • Some configurations may require external service credentials.
  • The repository's releases page currently states there are no releases.

Getting started

  1. Open the project repository on GitHub.
  2. Choose the Windows or Linux model-download instructions, or use the linked Colab script for an online experience.
  3. Prepare Python 3.10 and PyTorch 2.3.1.
  4. Use CUDA 11.8 or 12.1 as described in the setup instructions.
  5. Follow the local WebUI launch instructions.
  6. Provide Hugging Face or service credentials if required by your configuration.

Verdict

Choose Linly-Dubbing if you want an open-source video dubbing workflow with translation, voice options, and lip synchronization. Look elsewhere if you need a released version or do not want to set up the documented software and any required credentials.

Questions

Is Linly-Dubbing free?

The project is identified as open source, and its pricing model is free.

What operating systems does it support?

The listed platforms include Linux and Windows, as well as self-hosted and web use.

What license does it use?

The repository identifies the license as Apache License 2.0.

Does it support lip synchronization and speaker matching?

Yes. Lip synchronization and speaker matching are both listed. The project describes Linly-Talker technology for synchronizing dubbed speech with video visuals.

What setup does the project document?

Instructions use Python 3.10, PyTorch 2.3.1, and CUDA 11.8 or 12.1, with a local WebUI launch.

Could setup require credentials?

Depending on configuration, setup may use Hugging Face credentials or credentials for services such as OpenAI, Bytedance TTS, or Baidu.

Facts from Linly-Dubbing's own pages

External credentials
The setup guide lists optional credentials or tokens for OpenAI, Hugging Face, Bytedance TTS, and Baidu Ernie Bot, and says most users only need MODEL_NAME and HF_TOKEN. · github.com, 9 Oct 2026
Installation
The project is installed from its Git repository and launched as a local WebUI at 127.0.0.1:6006. · github.com, 9 Oct 2026
Languages
It supports dubbing and subtitle translation in Chinese and other languages. · github.com, 9 Oct 2026
License
The project is licensed under Apache License 2.0. · github.com, 9 Oct 2026
License and releases
The repository identifies the project as Apache License 2.0 and its releases page currently states that there are no releases. · github.com, 4 Oct 2026
Lip sync
The project integrates Linly-Talker's digital human lip-sync technology for synchronizing dubbing with video visuals. · github.com, 9 Oct 2026
Online option
The README links to a Colab script for an online experience. · github.com, 4 Oct 2026
Privacy and rights
The project asks users to comply with copyright, data protection, and privacy laws and not use the tool without the original author's or rights holder's permission. · github.com, 9 Oct 2026
Privacy and use
The project warns users to comply with copyright, data protection, and privacy laws and to obtain permission from rights holders. · github.com, 4 Oct 2026
Product
Linly-Dubbing is an intelligent multilingual AI dubbing and translation tool. · github.com, 9 Oct 2026
Requirements
The README says installation is very slow and requires configuring dependencies, downloading models, and setting environment variables. · github.com, 9 Oct 2026
Setup
The documented setup uses Python 3.10, PyTorch 2.3.1, and CUDA 11.8 or 12.1, with local WebUI launch instructions. · github.com, 4 Oct 2026
Speech recognition
It uses AI speech recognition for speech-to-text conversion and speaker recognition. · github.com, 9 Oct 2026
Speech synthesis
Documented speech synthesis options include Edge TTS, XTTS, CosyVoice, and GPT-SoVITS. · github.com, 9 Oct 2026
Supported environments
The installation instructions give Linux and Windows model-download commands and list test setups using Python 3.10, PyTorch 2.3.1, and CUDA 11.8 or 12.1. · github.com, 9 Oct 2026
Translation
The project describes translation through OpenAI models, locally run Qwen, and Google Translate. · github.com, 4 Oct 2026
Translations
Documented translation options include OpenAI models, local Qwen, and Google Translate. · github.com, 9 Oct 2026
Video download
The README describes automatic video and audio downloading with yt-dlp from YouTube and other sites. · github.com, 9 Oct 2026
Video downloads
The documentation describes automatic video downloading through yt-dlp, including support for YouTube and other websites. · github.com, 4 Oct 2026
Video processing
The tool can add subtitles and background music, adjust music volume, and change playback speed. · github.com, 4 Oct 2026
Video tools
Video processing can add subtitles and background music, adjust background music volume, and change playback speed. · github.com, 9 Oct 2026
Vocal separation
The project documents Demucs and UVR5 for separating vocals and accompaniment. · github.com, 4 Oct 2026
Voice cloning
Its listed features include AI voice cloning intended to match the original video's tone and emotion. · github.com, 9 Oct 2026
Voice synthesis
Documented speech synthesis options include Edge TTS, XTTS, CosyVoice, and GPT-SoVITS. · github.com, 4 Oct 2026

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