Speech to Text (Pulse)Features

Keyword Boosting

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Real-Time

Keyword boosting lets you bias the Pulse speech-to-text model toward specific words or phrases — useful for proper nouns, brand names, technical terms, or domain-specific vocabulary that the model might otherwise misrecognize.

Format

Keywords are passed as a single comma-separated string in the keywords query parameter. Each entry follows the format:

KEYWORD:INTENSIFIER
PartRequiredDescription
KEYWORDYesThe word or phrase to boost
INTENSIFIERNoA number controlling boost strength. Defaults to 1.0 if omitted

The value is a plain string, not a JSON array. Both of these shapes are wrong and produce garbled transcripts (the API parses the brackets and quotes as keyword characters):

❌ keywords=["I:20,smiling:26"]
❌ keywords=['I:20,smiling:26']

Pass it as one string instead:

✅ keywords=I:20,smiling:26

In JavaScript: url.searchParams.append("keywords", "I:20,smiling:26") — URLSearchParams URL-encodes the colons and comma for you. In Python: params = {"keywords": "I:20,smiling:26"} then urlencode(params) does the same. Verified against the live API.

Intensifier Scale

ValueEffect
1Mild boost (default if omitted)
2-3Moderate boost — good for uncommon proper nouns
4-6Strong boost — for rare terms the model struggles with
7-10Very strong boost — use sparingly, can over-bias results

Higher values create a stronger bias toward that word in the output. Start low and increase if the word still isn’t recognized correctly.

Enabling Keyword Boosting

Add the keywords query parameter to your WebSocket connection URL with a comma-separated list of keywords and optional intensifiers.

Single keyword

1const url = new URL("wss://api.smallest.ai/waves/v1/stt/live?model=pulse");
2url.searchParams.append("language", "en");
3url.searchParams.append("encoding", "linear16");
4url.searchParams.append("sample_rate", "16000");
5url.searchParams.append("keywords", "I:20,smiling:26");
6
7const ws = new WebSocket(url.toString(), {
8  headers: {
9    Authorization: `Bearer ${API_KEY}`,
10  },
11});

Multiple keywords

wss://api.smallest.ai/waves/v1/stt/live?model=pulse&language=en&encoding=linear16&sample_rate=16000&keywords=Hansi:6,Muller:6,CVV:9

Mix of boosted and default-intensity keywords

wss://api.smallest.ai/waves/v1/stt/live?model=pulse&language=en&encoding=linear16&sample_rate=16000&keywords=CEO:3,NVIDIA:5,Jensen

Jensen with no intensifier defaults to 1.0.

Examples

Boost names in a meeting transcript

wss://api.smallest.ai/waves/v1/stt/live?model=pulse&language=en&encoding=linear16&sample_rate=16000&keywords=Jensen:4,NVIDIA:5,Blackwell:6,CUDA:3

Boost brand names and product terms

wss://api.smallest.ai/waves/v1/stt/live?model=pulse&language=en&encoding=linear16&sample_rate=16000&keywords=Anthropic:5,Claude:4,Sonnet:3

Very high intensifiers (above 10) heavily bias the transcript and can hallucinate the keyword even when it was not spoken. The example I:20,smiling:26 demonstrates the format, not recommended values. Start at 3-6 and tune from there.

Limits

  • Max 100 keywords per session
  • Intensifier must be a non-negative number
  • Each keyword must be a string

Start with lower intensifier values (1–3) and increase gradually. Very high values (7–10) can over-bias the model and should be used sparingly.