collectiveai-team
/
crisperwhisper
Unofficial implementation of Verbatim Automatic Speech Recognition with improved word-level timestamps and filler detection
- Public
- 25 runs
- Paper
Run collectiveai-team/crisperwhisper with an API
Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.
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 |
|---|---|---|---|
| hf_token |
string
|
HuggingFace token to access CrispWhisper models.
|
|
| audio |
string
|
https://replicate.delivery/pbxt/IZjTvet2ZGiyiYaMEEPrzn0xY1UDNsh0NfcO9qeTlpwCo7ig/lex-levin-4min.mp3
|
Audio file
|
| language |
string
(enum)
|
None
Options: None, afrikaans, albanian, amharic, arabic, armenian, assamese, azerbaijani, bashkir, basque, belarusian, bengali, bosnian, breton, bulgarian, cantonese, catalan, chinese, croatian, czech, danish, dutch, english, estonian, faroese, finnish, french, galician, georgian, german, greek, gujarati, haitian creole, hausa, hawaiian, hebrew, hindi, hungarian, icelandic, indonesian, italian, japanese, javanese, kannada, kazakh, khmer, korean, lao, latin, latvian, lingala, lithuanian, luxembourgish, macedonian, malagasy, malay, malayalam, maltese, maori, marathi, mongolian, myanmar, nepali, norwegian, nynorsk, occitan, pashto, persian, polish, portuguese, punjabi, romanian, russian, sanskrit, serbian, shona, sindhi, sinhala, slovak, slovenian, somali, spanish, sundanese, swahili, swedish, tagalog, tajik, tamil, tatar, telugu, thai, tibetan, turkish, turkmen, ukrainian, urdu, uzbek, vietnamese, welsh, yiddish, yoruba |
Language spoken in the audio, specify 'None' to perform language detection.
|
| batch_size |
integer
|
8
|
Number of parallel batches you want to compute. Reduce if you face OOMs.
|
{
"type": "object",
"title": "Input",
"required": [
"hf_token"
],
"properties": {
"audio": {
"type": "string",
"title": "Audio",
"format": "uri",
"default": "https://replicate.delivery/pbxt/IZjTvet2ZGiyiYaMEEPrzn0xY1UDNsh0NfcO9qeTlpwCo7ig/lex-levin-4min.mp3",
"x-order": 1,
"description": "Audio file"
},
"hf_token": {
"type": "string",
"title": "Hf Token",
"x-order": 0,
"description": "HuggingFace token to access CrispWhisper models."
},
"language": {
"enum": [
"None",
"afrikaans",
"albanian",
"amharic",
"arabic",
"armenian",
"assamese",
"azerbaijani",
"bashkir",
"basque",
"belarusian",
"bengali",
"bosnian",
"breton",
"bulgarian",
"cantonese",
"catalan",
"chinese",
"croatian",
"czech",
"danish",
"dutch",
"english",
"estonian",
"faroese",
"finnish",
"french",
"galician",
"georgian",
"german",
"greek",
"gujarati",
"haitian creole",
"hausa",
"hawaiian",
"hebrew",
"hindi",
"hungarian",
"icelandic",
"indonesian",
"italian",
"japanese",
"javanese",
"kannada",
"kazakh",
"khmer",
"korean",
"lao",
"latin",
"latvian",
"lingala",
"lithuanian",
"luxembourgish",
"macedonian",
"malagasy",
"malay",
"malayalam",
"maltese",
"maori",
"marathi",
"mongolian",
"myanmar",
"nepali",
"norwegian",
"nynorsk",
"occitan",
"pashto",
"persian",
"polish",
"portuguese",
"punjabi",
"romanian",
"russian",
"sanskrit",
"serbian",
"shona",
"sindhi",
"sinhala",
"slovak",
"slovenian",
"somali",
"spanish",
"sundanese",
"swahili",
"swedish",
"tagalog",
"tajik",
"tamil",
"tatar",
"telugu",
"thai",
"tibetan",
"turkish",
"turkmen",
"ukrainian",
"urdu",
"uzbek",
"vietnamese",
"welsh",
"yiddish",
"yoruba"
],
"type": "string",
"title": "language",
"description": "Language spoken in the audio, specify 'None' to perform language detection.",
"default": "None",
"x-order": 2
},
"batch_size": {
"type": "integer",
"title": "Batch Size",
"default": 8,
"x-order": 3,
"description": "Number of parallel batches you want to compute. Reduce if you face OOMs."
}
}
}
Output schema
The shape of the response you’ll get when you run this model with an API.
{
"title": "Output"
}