vein: speech-to-text core — streaming dictation with hotwords - #1655
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… hotwords Streaming STT is the product surface; workflows learn around it (dream cycles), no STT step. src/audio/: service (model download+verify, cached recognizers, two-recognizer streams: fast greedy NeMo partials + hotword- capable Zipformer finals, batch transcribe), catalog, hotwords compiler (synthesized bpe.vocab — sherpa needs modelingUnit bpe or the list is a silent no-op), sessions + corrections, /audio/stream WebSocket (raw ws on the Node server; Bearer or ?key=), /audio/* routes. sherpa-onnx-node is an optionalDependency, lazy-loaded; routes answer 501 without it. Plan doc rewritten from the bake-off: measured latency/accuracy for kroko, NeMo fast-conformer 80/480 ms, Nemotron; NeMo online transducers are greedy-only in sherpa (no hotwords); sample-rate change aborts the process.
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What
Streaming speech-to-text inside vein over sherpa-onnx, per the rewritten §4 of
vein/plans/local-desktop-and-stt.md. Dictation over a WebSocket is the product surface; workflows sit around the recognizer as the learning loop ("dream cycles", §4.8). No STT workflow step in v1.src/audio/stt.ts— service: model download + sha256 verify +tar xjf, cached recognizers, streams (PCM16 in →partial/finalevents out), two-recognizer mode (fast greedy NeMo model for partials, hotword-capable Zipformer for finals + endpointing), batchtranscribe.sherpa-onnx-nodeis an optionalDependency, lazy-imported; without it/audio/*answers 501 and everything else is untouched.src/audio/hotwords.ts— contextual biasing. Two verified gotchas baked in: sherpa needsmodelingUnit: "bpe"(unset →cjkchar→ silent no-op), and abpe.vocabthe released models don't ship, synthesized fromtokens.txt. Named lists under<dataDir>/audio/hotwords/are the dream cycle's promotion artifact.src/audio/sessions.ts— finals + user corrections per session (training data for the dream cycle).src/audio/ws.ts—GET /audio/streamvia rawwson the Node server (@hono/node-wsdoesn't support node-server 2.x). Bearer or?key=.src/audio/routes.ts—/audio/models(+ SSE download),/audio/transcribe,/audio/hotwords/:name,/audio/sessions/:id(+ corrections).createVein({ stt }),ctx.services.stt,VEIN_MODEL_DIR(alias ofVEIN_MODEL_CACHE),VEIN_STT_MODEL,VEIN_STT_PARTIAL_MODEL.Measured (M-series Mac, see doc §4.1)
zipformer-en-kroko(57 MB)nemo-fast-conformer-en-80ms(103 MB)nemo-fast-conformer-en-480ms(106 MB)nemotron-speech-en-80ms(463 MB)End to end over the socket at real-time pace: partials 50–100 ms behind the audio, final ~300 ms after
end. Hotwords turned "on this FHIC swarm" into "on the Sphinx swarm" and "hive" into "Hive".Tests
npm run test:stt(opt-inVEIN_TEST_STT=1) downloads kroko and streams its bundled clip: 3/3 locally.