Аудио
buzz
Buzz transcribes and translates audio offline on your personal computer. Powered by OpenAI's Whisper.
★ 21,8 тыс. звёздMIT
Смотреть руководство →WhisperJAV — проект с открытым исходным кодом из категории «Локальные LLM» от meizhong986 (meizhong986/WhisperJAV на GitHub). У него 2 298 звёзд на GitHub и 195 форков, он распространяется по лицензии MIT и последний раз обновлялся на GitHub 17 сентября 2026.
Noise-robust subtitle generator powered by Whisper and local ASR models.
Set it up from the repo or releases.
Point it at the file needing subtitles.
ASR models generate the subtitle track.
Local LLMs clean up errors and hallucinations.
Strong baseline transcription quality.
Modern ASR model in the pipeline.
Handles difficult, noisy audio.
Voice activity detection trims silence.
Local LLMs refine raw transcripts.
Generates ready-to-use subtitle files.
Download the source and move into the project folder.
git clone https://github.com/meizhong986/WhisperJAV.git
cd WhisperJAVEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandJapanese is a focus; check the docs for the full language list.
MIT licensed — commercial use allowed.
ASR runs much faster with one; CPU is possible but slow.
A local LLM pass cleans up the raw ASR output.
Check the docs for supported output formats.
Buzz transcribes and translates audio offline on your personal computer. Powered by OpenAI's Whisper.
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Другие проекты из категории «Локальные LLM» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если WhisperJAV вам не подходит.
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Соседние проекты из категории «Локальные LLM» в каталоге, ближайшие по числу звёзд к WhisperJAV — продолжайте изучать полку по обе стороны от него.
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Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.