OptionalincludeAdditional information to include in the transcription response. logprobs will
return the log probabilities of the tokens in the response to understand the
model's confidence in the transcription. logprobs only works with
response_format set to json and only with the models gpt-4o-transcribe and
gpt-4o-mini-transcribe.
OptionallanguageThe language of the input audio. Supplying the input language in
ISO-639-1 (e.g. en)
format will improve accuracy and latency.
ID of the model to use. The options are gpt-4o-transcribe,
gpt-4o-mini-transcribe, and whisper-1 (which is powered by our open source
Whisper V2 model).
OptionalpromptAn optional text to guide the model's style or continue a previous audio segment. The prompt should match the audio language.
Optionalresponse_The format of the output, in one of these options: json, text, srt,
verbose_json, or vtt. For gpt-4o-transcribe and gpt-4o-mini-transcribe,
the only supported format is json.
OptionalstreamIf set to true, the model response data will be streamed to the client as it is generated using server-sent events. See the Streaming section of the Speech-to-Text guide for more information.
Note: Streaming is not supported for the whisper-1 model and will be ignored.
OptionaltemperatureThe sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use log probability to automatically increase the temperature until certain thresholds are hit.
Optionaltimestamp_The timestamp granularities to populate for this transcription.
response_format must be set verbose_json to use timestamp granularities.
Either or both of these options are supported: word, or segment. Note: There
is no additional latency for segment timestamps, but generating word timestamps
incurs additional latency.
The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.