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nicknaskida /whisper-diarization:240b90bd

Playground API

Input schema

The fields you can use to run this model with an API. If you don’t give a value for a field its default value will be used.

Field Type Default value Description
file_string
string
Either provide: Base64 encoded audio file,
file_url
string
Or provide: A direct audio file URL
file
string
Or an audio file
hf_token
string
Provide a hf.co/settings/token for Pyannote.audio to diarise the audio clips. You need to agree to the terms in 'https://huggingface.co/pyannote/speaker-diarization-3.1' and 'https://huggingface.co/pyannote/segmentation-3.0' first.
group_segments
boolean
True
Group segments of same speaker shorter apart than 2 seconds
transcript_output_format
string (enum)
both

Options:

words_only, segments_only, both

Specify the format of the transcript output: individual words with timestamps, full text of segments, or a combination of both.
num_speakers
integer
2

Min: 1

Max: 50

Number of speakers, leave empty to autodetect.
translate
boolean
False
Translate the speech into English.
language
string
Language of the spoken words as a language code like 'en'. Leave empty to auto detect language.
prompt
string
Vocabulary: provide names, acronyms and loanwords in a list. Use punctuation for best accuracy.
batch_size
integer
64

Min: 1

Batch size for inference. (Reduce if face OOM error)
offset_seconds
integer
0
Offset in seconds, used for chunked inputs

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema 
{'properties': {'language': {'title': 'Language', 'type': 'string'},
                'num_speakers': {'title': 'Num Speakers', 'type': 'integer'},
                'segments': {'items': {},
                             'title': 'Segments',
                             'type': 'array'}},
 'required': ['segments'],
 'title': 'Output',
 'type': 'object'}