Audio
silero-vad
Silero VAD: pre-trained enterprise-grade Voice Activity Detector
★ 10,3 Tsd. SterneMIT
Anleitung ansehen →cheetah ist ein Open-Source-Projekt aus der Kategorie Audio von Picovoice (Picovoice/cheetah auf GitHub). Es hat 670 Sterne auf GitHub und 77 Forks, wird unter der Lizenz Apache-2.0 veröffentlicht und wurde zuletzt am 2. Oktober 2026 auf GitHub aktualisiert.
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.
Die anderen Projekte der Kategorie Audio mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls cheetah nicht das Richtige ist.
利用 AI 大模型和自动化工作流，根据主题或关键词一键生成高清短视频。Generate HD short videos from a topic or keyword with an automated AI workflow.
Robust Speech Recognition via Large-Scale Weak Supervision
1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
Clone a voice from 5 seconds of audio and generate arbitrary speech in real time
Port of OpenAI's Whisper model in C/C++
Verwandte Projekte der Kategorie Audio im Katalog, die cheetah bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
Double-click any word for definitions, speech, translation, and Anki.
A macOS menu-bar dictation app powered by local WhisperKit.
Fully local transcription with diarization, for every desktop OS.
Open-source AI voice typing: hotkey, speak, get polished text anywhere.
Free AAC communication boards with text-to-speech, in the browser.
Give AI agents a seat in your meetings.
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.