{"data":{"slug":"r3gm-sonitranslate","name":"SoniTranslate","tagline":"Synchronized Translation for Videos. Video dubbing","github_url":"https://github.com/R3gm/SoniTranslate","owner":"R3gm","repo":"SoniTranslate","owner_avatar_url":"https://avatars.githubusercontent.com/u/114810545?v=4","primary_language":"Python","stars":1392,"forks":331,"topics":["asr","audio-processing","automatic-dubbing","diarization","document-translator","dubbing","speech-to-text","stt","subtitle-to-speech","text-to-speech","translate-audio","translate-video","translation","tts","video-dubbing"],"archived":false,"github_pushed_at":"2026-04-27T21:47:11+00:00","maintenance_label":"Steady","url":"https://www.graphcanon.com/tools/r3gm-sonitranslate","markdown_url":"https://www.graphcanon.com/tools/r3gm-sonitranslate.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/r3gm-sonitranslate","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=r3gm-sonitranslate","description":"Synchronized Translation for Videos. Video dubbing","homepage_url":null,"license":"Apache-2.0","open_issues":118,"watchers":25,"ai_summary":null,"readme_excerpt":"## Install Locally (Installation tested in Linux)\n\n---\n\n### Getting Started\n\nTo install SoniTranslate, follow these steps:\n\n1. Create a suitable anaconda environment for SoniTranslate and activate it:\n\n```\nconda create -n sonitr python=3.10 -y\nconda activate sonitr\npython -m pip install pip==23.1.2 Setuptools==80.6.0\nconda install pytorch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 pytorch-cuda=11.8 -c pytorch -c nvidia\n```\n\n2. Clone this github repository and navigate to it:\n```\ngit clone https://github.com/r3gm/SoniTranslate.git\ncd SoniTranslate\n```\n\n3. Install required packages:\n\n```\npip install -r requirements_base.txt -v\npip install -r requirements_extra.txt -v\npip install onnxruntime-gpu\n```\n\n4. Install [ffmpeg](https://ffmpeg.org/download.html). FFmpeg is a free software project that produces libraries and programs for handling multimedia data. You will need it to process audio and video files. You can install ffmpeg with Anaconda by running `conda install -y ffmpeg` in your terminal (recommended). If you have trouble installing ffmpeg via Anaconda, you can use the following link instead: (https://ffmpeg.org/ffmpeg.html). Once it is installed, make sure it is in your PATH by running `ffmpeg -h` in your terminal. If you don't get an error message, you're good to go.\n\n5. Optional install:\n\nAfter installing FFmpeg, you can install these optional packages.\n\n\n[Piper TTS](https://github.com/rhasspy/piper) is a fast, local neural text to speech system that sounds great and is optimized for the Raspberry Pi 4. Piper is used in a variety of projects. Voices are trained with VITS and exported to the onnxruntime.\n\n```\npip install -q piper-tts==1.2.0\n```\n\n[Coqui XTTS](https://github.com/coqui-ai/TTS) is a text-to-speech (TTS) model that lets you generate realistic voices in different languages. It can clone voices with just a short audio clip, even speak in a different language! It's like having a personal voice mimic for any text you need spoken.\n\n```\npip install -q -r requirements_xtts.txt\npip install -q TTS==0.21.1  --no-deps\n```\n\n---\n\n## License\nAlthough the code is licensed under Apache 2, the models or weights may have commercial restrictions, as seen with pyannote diarization.","github_created_at":"2023-06-27T22:32:23+00:00","created_at":"2026-07-11T12:11:46.135506+00:00","updated_at":"2026-07-11T12:11:59.110937+00:00","categories":[{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"},{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"}],"tags":[{"slug":"asr","name":"asr"},{"slug":"speech-to-text","name":"speech-to-text"},{"slug":"diarization","name":"diarization"},{"slug":"stt","name":"stt"},{"slug":"document-translator","name":"document-translator"},{"slug":"audio-processing","name":"audio-processing"},{"slug":"automatic-dubbing","name":"automatic-dubbing"},{"slug":"dubbing","name":"dubbing"}],"trust":{"provenance":{"is_fork":false,"github_id":659463960,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T12:11:46.894Z","maintenance":{"label":"Steady","score":60,"methodology":"github_public_v1","releases_90d":0,"days_since_push":74,"last_release_at":"2024-05-18T13:56:03Z"},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":87,"high_count":0,"last_scan_at":"2026-07-11T12:11:54.715Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-11T12:11:54.242Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-07-11T12:11:54.242Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-07-11T12:11:54.242Z"}}}}