Audio
silero-vad
Silero VAD: pre-trained enterprise-grade Voice Activity Detector
★ 10,3 k étoilesMIT
Voir le guide →cheetah est un projet de audio open source, créé par Picovoice (Picovoice/cheetah sur GitHub). Il compte 670 étoiles sur GitHub et 77 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 2 octobre 2026.
On-device streaming speech-to-text engine for real-time apps.
Choose the SDK for your target device.
Integrate the on-device STT library.
Feed live audio and receive transcripts in real time.
Live captions, commands, or dictation go live.
Recognition happens locally — no audio leaves the device.
Real-time transcripts as speech happens.
Neural models tuned for accuracy and speed.
Integrates across mobile, desktop, and embedded.
Built for responsive, live transcription features.
Commercial-friendly open-source terms.
Download the source and move into the project folder.
git clone https://github.com/Picovoice/cheetah.git
cd cheetahEvery 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 commandIt is an open-source project at Picovoice/cheetah with 77 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Apache 2.0 licensed — commercial use allowed with attribution.
No — it is an on-device engine by design.
Streaming — it produces transcripts in real time as speech arrives.
Picovoice targets mobile, desktop, and embedded platforms — check the docs.
Silero VAD: pre-trained enterprise-grade Voice Activity Detector
A robust, efficient, low-latency speech-to-text library with advanced voice activity detection, wake word activation and instant transcription.
Silero Models: pre-trained text-to-speech models made embarrassingly simple
MOSS-TTS family: open text-to-speech models for voice cloning, dialogue, voice design, and real-time agents
GAN vocoder that turns mel-spectrograms into high-fidelity speech audio, fast enough for real-time use.
On-device speech-to-text for macOS.
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Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.