Create transcription session

Request body

• modalities

  object

  The set of modalities the model can respond with. To disable audio, set this to ["text"].

• input_audio_format

  string

  Defaults: pcm16

  The format of input audio. Options are pcm16, g711_ulaw, or g711_alaw. For pcm16, input audio must be 16-bit PCM at a 24kHz sample rate, single channel (mono), and little-endian byte order.

  Show possible types

  • pcm16

    string

  • g711_ulaw

    string

  • g711_alaw

    string

• input_audio_transcription

  object

  Configuration for input audio transcription. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.
  Show properties

  • model

    string

    The model to use for transcription, current options are gpt-4o-transcribe, gpt-4o-mini-transcribe, and whisper-1.

    Show possible types

    • gpt-4o-transcribe

      string

    • gpt-4o-mini-transcribe

      string

    • whisper-1

      string

  • language

    string

    The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

  • prompt

    string

    An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models, the prompt is a free text string, for example "expect words related to technology".

• turn_detection

  object

  Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to 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.

  Show properties

  • type

    string

    Defaults: server_vad

    Type of turn detection.
    Show possible types

    • server_vad

      string

    • semantic_vad

      string

  • eagerness

    string

    Defaults: auto

    Used 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.

    Show possible types

    • low

      string

    • medium

      string

    • high

      string

    • auto

      string

  • threshold

    number

    Used 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.

  • prefix_padding_ms

    integer

    Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

  • silence_duration_ms

    integer

    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.

  • create_response

    boolean

    Defaults: true

    Whether or not to automatically generate a response when a VAD stop event occurs. Not available for transcription sessions.

  • interrupt_response

    boolean

    Defaults: true

    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.

• input_audio_noise_reduction

  object

  Defaults: null

  Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

  Show properties

  • type

    string

    Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

    Show possible types

    • near_field

      string

    • far_field

      string

• include

  array

  The set of items to include in the transcription. Current available items are:

  • item.input_audio_transcription.logprobs
  Show possible types

  • items

    string

Response