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openai/whisper-small.en cover image

openai/whisper-small.en

Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation, trained on 680k hours of labelled data without the need for fine-tuning. It is a Transformer based encoder-decoder model, trained on either English-only or multilingual data, and is available in five configurations of varying model sizes. The models were trained on the tasks of speech recognition and speech translation, predicting transcriptions in the same or different languages as the audio.

Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation, trained on 680k hours of labelled data without the need for fine-tuning. It is a Transformer based encoder-decoder model, trained on either English-only or multilingual data, and is available in five configurations of varying model sizes. The models were trained on the tasks of speech recognition and speech translation, predicting transcriptions in the same or different languages as the audio.

Public

HTTP/cURL API

You can use cURL or any other http client to run inferences:

curl -X POST \
    -H "Authorization: bearer $DEEPINFRA_TOKEN"  \
    -F audio=@my_voice.mp3  \
    'https://api.deepinfra.com/v1/inference/openai/whisper-small.en'
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which will give you back something similar to:

{
  "text": "",
  "segments": [
    {
      "end": 1.0,
      "id": 0,
      "start": 0.0,
      "text": "Hello"
    },
    {
      "end": 5.0,
      "id": 1,
      "start": 4.0,
      "text": "World"
    }
  ],
  "language": "en",
  "input_length_ms": 0,
  "words": [
    {
      "end": 1.0,
      "start": 0.0,
      "text": "Hello"
    },
    {
      "end": 5.0,
      "start": 4.0,
      "text": "World"
    }
  ],
  "duration": 0.0,
  "request_id": null,
  "inference_status": {
    "status": "unknown",
    "runtime_ms": 0,
    "cost": 0.0,
    "tokens_generated": 0,
    "tokens_input": 0
  }
}

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Input fields

audiostring

audio to transcribe


taskstring

task to perform

Default value: "transcribe"

Allowed values: transcribetranslate


initial_promptstring

optional text to provide as a prompt for the first window.


temperaturenumber

temperature to use for sampling

Default value: 0


languagestring

language that the audio is in; uses detected language if None; use two letter language code (ISO 639-1) (e.g. en, de, ja)

Allowed values: afamarasazbabebgbnbobrbscacscydadeeleneseteufafifofrglguhahawhehihrhthuhyidisitjajwkakkkmknkolalblnloltlvmgmimkmlmnmrmsmtmynenlnnnoocpaplpsptrorusasdsiskslsnsosqsrsusvswtatetgthtktltrttukuruzviyiyoyuezh


chunk_levelstring

chunk level, either 'segment' or 'word'

Default value: "segment"

Allowed values: segmentword


chunk_length_sinteger

chunk length in seconds to split audio

Default value: 30

Range: 1 ≤ chunk_length_s ≤ 30


webhookfile

The webhook to call when inference is done, by default you will get the output in the response of your inference request

Input Schema

Output Schema