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

Real-Time WebSocket API

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/pulse/get_text");
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/pulse/get_text?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/pulse/get_text?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/pulse/get_text?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/pulse/get_text?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.