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tern is an open-source audio project by B0yko (B0yko/tern on GitHub). It has 81 GitHub stars and 0 forks, is released under the NOASSERTION license, and was last updated on GitHub on 29 September 2026.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
Runs on your own machine; your data never leaves it.
Turns spoken audio into accurate text.
Built on Whisper for accurate speech recognition.
Handles MP3, WAV, and common audio formats.
Real-time transcription as audio arrives.
Faster processing with CUDA support.
Download the source and move into the project folder.
git clone https://github.com/B0yko/tern.git
cd ternCreate a virtual environment and install the requirements.
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtStart the app or CLI and follow the README examples.
python main.py --helpIt is an open-source project at B0yko/tern with 0 forks. Check the repo’s contributors and recent commits to judge how active maintenance is.
GitHub does not assert a license for this repo, so treat the code as all rights reserved until the author adds one.
MP3, WAV, and most common formats are supported.
It helps a lot for transcription speed, but CPU mode works too.
Tools with diarization label who said what.
Give AI agents a seat in your meetings.
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The most-starred other Audio projects in the LibreAI catalogue — the realistic shortlist if tern is not the right fit.
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1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
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Port of OpenAI's Whisper model in C/C++
Free and open — grab the source, star the repo, and start creating.