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Awesome GitHub RepositoriesVideo Localization Platforms

Integrated systems for transcribing, translating, and dubbing video media.

Distinct from Automated Video Synthesis: Distinct from automated video synthesis: focuses on localizing existing media rather than creating new video content from scratch.

Explore 6 awesome GitHub repositories matching artificial intelligence & ml · Video Localization Platforms. Refine with filters or upvote what's useful.

Awesome Video Localization Platforms GitHub Repositories

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  • jianchang512/pyvideotransjianchang512 的头像

    jianchang512/pyvideotrans

    17,991在 GitHub 上查看↗

    Pyvideotrans is an automated video localization platform designed to transcribe, translate, and dub media content for international distribution. It functions as an end-to-end workflow that combines speech recognition, text translation, and synthetic voice generation to process video files into localized versions. The system distinguishes itself by offering a choice between local model inference for privacy and integration with third-party cloud services via user-provided credentials. This architecture allows users to maintain control over their billing and data security while utilizing modul

    Automates the end-to-end process of transcribing, translating, and dubbing video media using speech recognition and synthesis.

    Pythonspeech-to-texttext-to-speechvideo-transition
    在 GitHub 上查看↗17,991
  • huanshere/videolingoHuanshere 的头像

    Huanshere/VideoLingo

    17,498在 GitHub 上查看↗

    VideoLingo is an automated video localization suite designed to transcribe, translate, and dub video content. It functions as a translation pipeline that utilizes large language models to convert spoken audio into precise text segments and translate them into multiple languages. The system differentiates itself through a multi-step translation refinement process and a specialized natural language processing utility that segments text into single-line captions meeting broadcast standards. It also integrates synthetic voiceover generation to replace or augment original audio tracks. The projec

    An integrated platform for transcribing, translating, and dubbing video media for localization.

    Pythonai-translationdubbinglocalization
    在 GitHub 上查看↗17,498
  • krillinai/krillinaikrillinai 的头像

    krillinai/KrillinAI

    9,396在 GitHub 上查看↗

    KrillinAI is an AI video localization pipeline and toolset designed to automate the process of transcribing, translating, and dubbing video content into multiple languages. It provides a command-line interface to chain these stages into a single production workflow, coordinating speech-to-text transcription, translation, and audio generation. The system features a translation framework that uses large language models to maintain professional terminology and natural semantics rather than literal word replacement. It includes a dubbing tool that utilizes text-to-speech and voice cloning to gene

    Provides an integrated system for transcribing, translating, and dubbing video content into multiple languages.

    Godubbinglocalizationtts
    在 GitHub 上查看↗9,396
  • tmelyralab/musetalkTMElyralab 的头像

    TMElyralab/MuseTalk

    5,327在 GitHub 上查看↗

    MuseTalk is a deep learning lip synchronization system designed to align video facial movements with audio tracks for high-fidelity video dubbing. It functions as an engine that matches facial expressions to audio input in real-time, enabling the modification of a speaker's lip movements to match new audio sources across different languages. The project features a distributed GPU training pipeline and a multi-stage processing workflow for refining the visual accuracy of synthetic speech. It distinguishes itself through the use of region-specific face masking and mouth openness control, which

    Adapts visual speech patterns in video to match the phonetics of different languages during localization.

    Pythonlip-syncvirtualhumans
    在 GitHub 上查看↗5,327
  • liuzhao1225/youdub-webuiliuzhao1225 的头像

    liuzhao1225/YouDub-webui

    3,957在 GitHub 上查看↗

    YouDub-webui is a multilingual video translator and AI dubbing pipeline manager featuring a web interface for automating video translation, audio dubbing, and subtitle burning. It utilizes a GPU-accelerated media processor to speed up audio transcription and video rendering tasks. The system implements a stage-based pipeline that converts original speech into new languages while preserving background audio through audio track mixing. It supports multiple localization workflows, including automated translation and subtitle-driven dubbing using SRT files to bypass automatic transcription phases

    Provides an integrated platform for transcribing, translating, and dubbing videos automatically.

    Python
    在 GitHub 上查看↗3,957
  • kedreamix/linly-dubbingKedreamix 的头像

    Kedreamix/Linly-Dubbing

    3,048在 GitHub 上查看↗

    Linly-Dubbing is an automated video dubbing pipeline designed for multilingual video localization. It converts spoken content in videos into another language by coordinating speech-to-text transcription, text translation, and text-to-speech synthesis. The system distinguishes itself through AI-driven lip synchronization and animation, which aligns facial expressions and mouth movements to the synthesized voiceover. It also utilizes audio source separation to isolate vocals from background music and noise, allowing for clean voice replacement while preserving original background audio. The br

    Localizes video content for international audiences via transcription, translation, and synthetic dubbing.

    Jupyter Notebook
    在 GitHub 上查看↗3,048
  1. Home
  2. Artificial Intelligence & ML
  3. Video Localization Platforms

探索子标签

  • Command Line InterfacesCommand-line tools for managing and executing automated media localization workflows. **Distinct from Video Localization Platforms:** Provides the specific CLI orchestration layer for localization platforms rather than the underlying platform logic itself.
  • Subtitle-Based LocalizationLocalization workflows that use provided subtitle files to bypass automatic transcription. **Distinct from Video Localization Platforms:** Focuses on the specific workflow of using existing SRT/text files for dubbing instead of automated recognition.