Transcribes audio into the input language.
POST /audio/transcriptions
Authorizations
Request Body required
object
The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.
The language of the input audio. Supplying the input language in ISO-639-1 format will improve accuracy and latency.
An optional text to guide the model’s style or continue a previous audio segment. The prompt should match the audio language.
The format of the output, in one of these options: json
, text
, srt
, verbose_json
, or vtt
.
The 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.
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.
Responses
200
OK
Represents a transcription response returned by model, based on the provided input.
object
The transcribed text.
Represents a verbose json transcription response returned by model, based on the provided input.
object
The language of the input audio.
The duration of the input audio.
The transcribed text.
Extracted words and their corresponding timestamps.
object
The text content of the word.
Start time of the word in seconds.
End time of the word in seconds.
Segments of the transcribed text and their corresponding details.
object
Unique identifier of the segment.
Seek offset of the segment.
Start time of the segment in seconds.
End time of the segment in seconds.
Text content of the segment.
Array of token IDs for the text content.
Temperature parameter used for generating the segment.
Average logprob of the segment. If the value is lower than -1, consider the logprobs failed.
Compression ratio of the segment. If the value is greater than 2.4, consider the compression failed.
Probability of no speech in the segment. If the value is higher than 1.0 and the avg_logprob
is below -1, consider this segment silent.