🎙️RealtimeSTT
A robust, efficient, low-latency speech-to-text library with advanced voice activity detection, wake word activation and instant transcription.
⭐ Very popular: 10k stars, gaining about 13 a week
View on GitHub ↗repo profile
momentum
durability
bus factor = how many people it takes to cover more than half the commits (6 months). 1 is a solo project; higher means the work is spread across a team. top-author share is the single busiest author's slice of those commits.
since we covered it
why it's a big deal
- Gives developers a ready-made speech-to-text layer for voice assistants and live transcription, handling the awkward parts like knowing when someone starts and stops speaking.
- Optional wake word activation via Porcupine or OpenWakeWord means an app can idle until called, useful for hands-free interfaces without keeping full transcription running.
- Runs across Linux, macOS and Windows with microphone, file, stream and websocket input, so it fits both desktop apps and browser streaming setups.
under the hood
- Python library defaulting to faster_whisper for transcription, with swappable engines including OpenAI Whisper, whisper.cpp, Moonshine, sherpa-onnx and Parakeet NeMo.
- Voice activity detection uses WebRTC VAD and Silero VAD, and audio is handled as 16-bit mono PCM at 16 kHz with optional resampling.
- Uses multiprocessing to isolate model inference and exposes event callbacks for recording, VAD, realtime text and wake word state, with optional CUDA and a FastAPI browser streaming example.
Radar summary, generated from the project's public sources
star history
- PR#11 8k 2025-06-25
- now 10k + 2k since first covered
curve is sampled from GitHub's star history, plus our own daily readings since we covered it; the dashed stretch is before we first covered it, the solid line since. figures at coverage are the numbers we printed then (approx.), current count is live.
understory
Output and attention are roughly in balance.
- output, commits & releases
- clout, star velocity
output = commits & releases; clout = star velocity, both 0 to 100 monthly indices; the gap where output runs above clout is the understory. The understory →
covered in
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Low-Latency Speech-to-Text with Wake Word Activation
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