Universal-3 Pro Streaming

The speech model to use.

Use your API key for authentication, or alternatively generate a temporary token and pass it via the token query parameter.

Encoding of the audio stream.

Optional time in seconds of inactivity before session is terminated (integer, minimum 5, maximum 3600). If not set, no inactivity timeout is applied.

A list of words and phrases to improve recognition accuracy for. See Keyterms Prompting for more details.

Whether to return language_code and language_confidence in turn messages. Universal-3 Pro Streaming natively code-switches between English, Spanish, German, French, Portuguese, and Italian by default without any necessary configuration.

Maximum silence in milliseconds before the turn is forced to end, regardless of punctuation. See Configuring Turn Detection for configuration details.

Silence duration in milliseconds before a speculative end-of-turn check. If terminal punctuation is found, the turn ends. Otherwise, a partial is emitted and the turn continues. See Configuring Turn Detection for configuration details.

Prompting is a beta feature. Custom transcription instructions for the model. When not provided, a default prompt optimized for native turn detection is used automatically. See the Prompting Guide for details.

Sample rate of the audio stream.

Whether to enable Streaming Speaker Diarization. When enabled, each Turn event will include a speaker_label field and each final word in the words array will include a speaker field for word-level speaker attribution.

The maximum number of speakers expected in the audio stream (integer, 1-10). Setting this can improve speaker label accuracy when you know the number of speakers in advance. Only used when speaker_labels is enabled. See Streaming Diarization for more details.

API token for authentication (if using a temporary token).

The confidence threshold (0.0 to 1.0) for classifying audio frames as silence. Frames with VAD confidence below this value are considered silent. Increase for noisy environments to reduce false speech detection.

Whether to emit additional partial transcripts during long turns at a steady ~3 second cadence. When disabled (default), only one early partial is emitted near turn start. When enabled, additional partials covering the full turn transcript are emitted approximately every 3 seconds while speech continues. The first partial (at 750ms) is unaffected.

Whether to emit partial transcripts during the turn. When enabled (default), partial transcripts are forwarded as speech is still in progress alongside final turns. When disabled, only final turns (with end_of_turn true) are sent. Defaults to false when redact_pii is enabled, to prevent unredacted partial transcripts from reaching the client; set explicitly to true to override.

How soon the first partial is emitted in milliseconds. Useful for tuning voice agent barge-in responsiveness or allowing earlier partials for early LLM inference. Larger values are more confident on interruptions, smaller values result in faster time to first partial.

Enable domain-specific transcription models to improve accuracy for specialized terminology. Set to "medical-v1" to enable Medical Mode for improved accuracy of medical terms such as medications, procedures, conditions, and dosages. Supported languages: English (en), Spanish (es), German (de), French (fr). If used with an unsupported language, the parameter is ignored and a warning is returned.

Filter profanity from the transcribed text, can be true or false. See Profanity Filtering for more details.

Redact PII from the transcribed text using the Redact PII model, can be true or false. Only applies to final turns. See PII Redaction for more details.

The list of PII Redaction policies to enable. Requires redact_pii to be true. See PII redaction for more details.

The replacement logic for detected PII, can be entity_name or hash. Requires redact_pii to be true. See PII redaction for more details.

JSON-stringified LLM Gateway configuration that processes each finalized turn. Follows the same interface as the Chat Completions endpoint and accepts model, messages, tools, tool_choice, post_processing_steps, and max_tokens. See Apply LLM Gateway to Streaming for the full schema and examples.