Optionalcreate_Whether or not to automatically generate a response when a VAD stop event occurs. Not available for transcription sessions.
OptionaleagernessUsed only for semantic_vad mode. The eagerness of the model to respond. low
will wait longer for the user to continue speaking, high will respond more
quickly. auto is the default and is equivalent to medium.
Optionalinterrupt_Whether or not to automatically interrupt any ongoing response with output to
the default conversation (i.e. conversation of auto) when a VAD start event
occurs. Not available for transcription sessions.
Optionalprefix_Used only for server_vad mode. Amount of audio to include before the VAD
detected speech (in milliseconds). Defaults to 300ms.
Optionalsilence_Used only for server_vad mode. Duration of silence to detect speech stop (in
milliseconds). Defaults to 500ms. With shorter values the model will respond
more quickly, but may jump in on short pauses from the user.
OptionalthresholdUsed only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this
defaults to 0.5. A higher threshold will require louder audio to activate the
model, and thus might perform better in noisy environments.
OptionaltypeType of turn detection.
Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to
nullto turn off, in which case the client must manually trigger model response. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech. Semantic VAD is more advanced and uses a turn detection model (in conjuction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.