transcription_create_params
Classes:
Name | Description |
---|---|
TranscriptionCreateParams |
|
TranscriptionCreateParams
Attributes:
Name | Type | Description |
---|---|---|
file |
Required[FileTypes]
|
The audio file object (not file name) to transcribe, in one of these formats: |
language |
str
|
The language of the input audio. |
model |
Required[Union[str, Literal['whisper-1']]]
|
ID of the model to use. |
prompt |
str
|
An optional text to guide the model's style or continue a previous audio |
response_format |
Literal['json', 'text', 'srt', 'verbose_json', 'vtt']
|
The format of the transcript output, in one of these options: |
temperature |
float
|
The sampling temperature, between 0 and 1. |
timestamp_granularities |
List[Literal['word', 'segment']]
|
The timestamp granularities to populate for this transcription. |
file
instance-attribute
The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.
language
instance-attribute
language: str
The language of the input audio.
Supplying the input language in ISO-639-1 format will improve accuracy and latency.
model
instance-attribute
ID of the model to use.
Only whisper-1
(which is powered by our open source Whisper V2 model) is
currently available.
prompt
instance-attribute
prompt: str
An optional text to guide the model's style or continue a previous audio segment.
The prompt should match the audio language.
response_format
instance-attribute
The format of the transcript output, in one of these options: json
, text
,
srt
, verbose_json
, or vtt
.
temperature
instance-attribute
temperature: float
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.
timestamp_granularities
instance-attribute
timestamp_granularities: List[Literal['word', 'segment']]
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.