metadata

license: apache-2.0
language:
  - en
  - zh
  - de
  - es
  - ru
  - ko
  - fr
  - ja
  - pt
  - tr
  - pl
  - ca
  - nl
  - ar
  - sv
  - it
  - id
  - hi
  - fi
  - vi
  - he
  - uk
  - el
  - ms
  - cs
  - ro
  - da
  - hu
  - ta
  - 'no'
  - th
  - ur
  - hr
  - bg
  - lt
  - la
  - mi
  - ml
  - cy
  - sk
  - te
  - fa
  - lv
  - bn
  - sr
  - az
  - sl
  - kn
  - et
  - mk
  - br
  - eu
  - is
  - hy
  - ne
  - mn
  - bs
  - kk
  - sq
  - sw
  - gl
  - mr
  - pa
  - si
  - km
  - sn
  - yo
  - so
  - af
  - oc
  - ka
  - be
  - tg
  - sd
  - gu
  - am
  - yi
  - lo
  - uz
  - fo
  - ht
  - ps
  - tk
  - nn
  - mt
  - sa
  - lb
  - my
  - bo
  - tl
  - mg
  - as
  - tt
  - haw
  - ln
  - ha
  - ba
  - jw
  - su
tags:
  - audio
  - automatic-speech-recognition
  - hf-asr-leaderboard
base_model: openai/whisper-small
pipeline_tag: automatic-speech-recognition
model-index:
  - name: whisper-small
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: LibriSpeech (clean)
          type: librispeech_asr
          config: clean
          split: test
          args:
            language: en
        metrics:
          - name: Test WER
            type: wer
            value: 3.432213777886737

Whisper-small OpenVINO IR

Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. Trained on 680k hours of labelled data, Whisper models demonstrate a strong ability to generalise to many datasets and domains without the need for fine-tuning.

Whisper was proposed in the paper Robust Speech Recognition via Large-Scale Weak Supervision by Alec Radford et al from OpenAI. The original code repository can be found here.

Disclaimer: Content for this model card has partly been copied and pasted from this model card.

Model details

Whisper is a Transformer based encoder-decoder model, also referred to as a sequence-to-sequence model. This model architecture is used in THIS REPO(Intel)

Model Type	n_vocab	n_audio_ctx	n_audio_state	n_audio_head	n_audio_layer	n_text_ctx	n_text_state	n_text_head	n_text_layer	n_mels	Parameters
whisper_tiny	51864	1500	512	6	4	128	512	6	4	80	39 M
whisper_tiny.en	51864	1500	512	6	4	128	512	6	4	80	39 M
whisper_base	51864	1500	512	8	6	128	512	8	6	80	74 M
whisper_base.en	51864	1500	512	8	6	128	512	8	6	80	74 M
whisper_small	51864	1500	512	12	12	128	512	12	12	80	244 M
whisper_small.en	51864	1500	512	12	12	128	512	12	12	80	244 M
whisper_medium	51864	1500	512	16	24	128	512	16	16	80	769 M
whisper_medium.en	51864	1500	512	16	24	128	512	16	16	80	769 M
whisper_large_v1	51864	1500	512	20	32	128	512	20	20	80	1550 M
whisper_large_v2	51864	1500	512	20	32	128	512	20	20	80	1550 M
whisper_large_v3	51864	1500	512	20	32	128	512	20	20	80	1550 M