Run the complete example. A browser live-captions demo, scaffolded in one
command, no clone:Or browse it:
browser-hear-live-captions.Endpoint:
wss://api.pyai.com/v1/audio/transcriptions/stream?protocol=pyai-hear-v1. The full wire
protocol, query params, the JSON frame schema, the {"type":"commit"} flush, and
close codes, is published in the API reference
(GET /v1/audio/transcriptions/stream, generated from
https://api.pyai.com/openapi.json) and summarized in
Wire protocol below. Last verified 2026-06-16 against
api.pyai.com.How it fits together
One socket carries two things: you send binary PCM16 audio frames up, and receive text JSON result frames down. Results come in two flavors, fast-but-revisable partials and stable finals, and your UI’s whole job is to show the former without committing to them, then lock in the latter.Streaming vs. batch, pick the right tool
Audio format: PCM16 at 8 or 16 kHz
Hear streaming consumes PCM16 little-endian mono at 8 or 16 kHz. Setsample_rate to the actual rate of the bytes you send; the default is
16000. Hear converts 8 kHz input before recognition and endpointing.
Other sample rates and compressed encodings are rejected before the WebSocket
opens with 400 unsupported_audio_format.
- Browser mic typically runs the
AudioContextat 48 kHz. Either request a 16 kHz context, or decimate 3:1 on capture (48000 / 16000 = 3) before sending. - Telephony is usually 8 kHz. Decode μ-law to PCM16 first, then send it with
sample_rate=8000, or resample it to 16 kHz and declaresample_rate=16000. - Frame size: ~20 ms per message (160 samples at 8 kHz; 320 at 16 kHz) keeps latency low without paying per-message overhead.
capture-processor.js, Float32 → PCM16 @ 16 kHz
The two-pass display pattern
This is the heart of a good live-transcription UI. Treat the transcript as a list of committed final lines plus one pending partial at the end:- A partial arrives → render it greyed/italic as the “current” line. Partials are revisable, replace, never append.
- A newer partial arrives → overwrite the same pending line.
- A final arrives → commit it as solid text and clear the pending line.
- Repeat for the next phrase.
Two-pass transcript renderer
Wire protocol
Connect. Open a WebSocket to the streaming transcription endpoint and pick your audio format with query params:protocol=pyai-hear-v1 selects the published bare frame names used throughout
this guide. It is the only Hear streaming protocol; omitting the parameter uses
the same pyai-hear-v1 default.
Authenticate the upgrade with your key as a subprotocol (browser-safe):
Sec-WebSocket-Protocol: pyai.v1, pyai-key.<API_KEY>, server-side clients may use
?api_key= instead. The key needs the hear:stream scope.
With an explicit English hint, final transcripts apply number formatting by default (phones,
currency, dates, ordinals). Send
numerals=false to keep spoken form, or
numerals=true to force digits. Interim partials are never rewritten. Automatic mode may retain spoken number forms.Add &smart_format=true (or smartFormat: true in the SDK) for punctuation
and sentence capitalization on finals only. Optional extras, also finals-only
and off by default: dictation (spoken period / comma / new paragraph /
question mark), drop_fillers (um / uh / er; do not enable on legal
or compliance audio by default), and vocabulary for known terms. Send terms
for one session or explicitly enable the stored hear_stream profile. See
Format Hear transcripts.
These English cleanup flags are conservative/no-op where unsupported on
non-English transcripts. The underlying transcript language remains pinned.sample_rate=8000 or sample_rate=16000), ~20 ms each. To force-finalize the
current utterance, e.g. when your own VAD detects end-of-turn, send a JSON text
frame {"type":"commit"}. Closing the socket also flushes a final.
Server → client. JSON text frames, emitted with bare type names:
utterance_id groups the partials and finals of one phrase; t_ms is the audio
position of the hypothesis; audio_ms is the utterance’s active-speech length.
endpoint_reason is peak_te_early when the high-confidence path fires or
silence_backstop when the bounded fallback closes the turn. Log it when tuning
conversational pacing.
Close codes. 1000 normal · 1008 auth/policy (bad key or missing
hear:stream scope) · 1011 engine error · 4429 over the concurrency cap.
An error frame with code: recognition_interrupted, followed by close 1011,
means accepted audio could not be fully recovered. Treat the session as
incomplete and start a new stream. An earlier final completes its own
utterance; it does not prove that later audio was recognized. Do not treat an
error close as success because an earlier final exists.
Connection retries are limited to before caller PCM is accepted. Hear does not
silently replay missing audio or produce further transcript results or automatic
Recap from an interrupted session.
Wire it up
Open the socket, stream capture frames as binary, and route text frames through one handler. Authenticate the upgrade with the key as a subprotocol, the browser-safe pattern that’s stable across PyAI’s realtime surfaces (server-side clients may use?api_key= instead).
Connect + route frames
partial as revisable UI. Commit final. speech_final arrives first
with endpoint_reason; treat it as a stable preview of the same utterance, not
a second committed line.
Force-finalize and handle frames
The endpoint path, the frame schema, and the
{"type":"commit"} control message
are part of the published contract, see the API reference
(GET /v1/audio/transcriptions/stream) or the Wire protocol
summary above. Keep all framing inside handleFrame so adding a field later is a
one-place change.speech_final and final describe the same completed utterance.
speech_final is the immediate stable result; final follows with the
full-context correction. If your UI commits both, key rows by utterance_id and
replace the first value. Do not append both as separate transcript lines.Latency expectations
- First partial: sub-second. Once audio is flowing you should see an initial partial within a few hundred milliseconds, that immediacy is the entire point of streaming.
- Finals lag partials slightly. A phrase finalizes once the recognizer is confident (typically at a pause or end of utterance). This is normal, show partials so the UI never feels stalled while waiting for a final.
- Keep frames small and steady. 20 ms frames sent as they’re produced minimize end-to-end latency; don’t batch several seconds of audio into one message.
- Don’t add your own buffering on top. Send frames straight from the capture worklet; extra queues only add delay.
Troubleshooting
Next steps
Telephony audio (8 kHz μ-law)
Stream phone-call audio into Hear: native μ-law and the exact resample ratios.
Timestamped recording jobs
When the audio is finished, batch-transcribe with word/segment offsets and diarization.
Browser voice agent
The same PCM16 capture pipeline, driving a full-duplex Omni agent.
Errors & limits
Close codes, rate limits, and concurrency.