Automatic Speech Recognition
Transformers
Safetensors
Japanese
whisper
audio
hf-asr-leaderboard
Eval Results
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@@ -19,7 +19,7 @@ pipeline_tag: automatic-speech-recognition
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  metrics:
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  - wer
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  model-index:
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- - name: kotoba-tech/kotoba-whisper-v1.0
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  results:
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  - task:
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  type: automatic-speech-recognition
@@ -29,10 +29,10 @@ model-index:
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  metrics:
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  - name: WER
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  type: WER
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- value: 59.27
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  - name: CER
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  type: CER
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- value: 9.44
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  - task:
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  type: automatic-speech-recognition
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  dataset:
@@ -41,10 +41,10 @@ model-index:
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  metrics:
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  - name: WER
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  type: WER
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- value: 56.62
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  - name: CER
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  type: CER
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- value: 12.60
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  - task:
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  type: automatic-speech-recognition
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  dataset:
@@ -53,13 +53,13 @@ model-index:
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  metrics:
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  - name: WER
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  type: WER
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- value: 64.36
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  - name: CER
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  type: CER
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- value: 8.48
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  ---
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- # Kotoba-Whisper
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  _Kotoba-Whisper_ is a collection of distilled [Whisper](https://arxiv.org/abs/2212.04356) models for Japanese ASR, developed through the collaboration bewteen
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  [Asahi Ushio](https://asahiushio.com) and [Kotoba Technologies](https://twitter.com/kotoba_tech).
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  Following the original work of distil-whisper ([Robust Knowledge Distillation via Large-Scale Pseudo Labelling](https://arxiv.org/abs/2311.00430)),
 
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  metrics:
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  - wer
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  model-index:
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+ - name: kotoba-tech/kotoba-whisper-v2.0
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  results:
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  - task:
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  type: automatic-speech-recognition
 
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  metrics:
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  - name: WER
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  type: WER
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+ value: 58.9
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  - name: CER
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  type: CER
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+ value: 9.20
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  - task:
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  type: automatic-speech-recognition
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  dataset:
 
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  metrics:
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  - name: WER
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  type: WER
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+ value: 55.6
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  - name: CER
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  type: CER
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+ value: 11.63
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  - task:
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  type: automatic-speech-recognition
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  dataset:
 
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  metrics:
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  - name: WER
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  type: WER
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+ value: 63.8
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  - name: CER
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  type: CER
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+ value: 8.40
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  ---
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+ # Kotoba-Whisper (v2.0)
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  _Kotoba-Whisper_ is a collection of distilled [Whisper](https://arxiv.org/abs/2212.04356) models for Japanese ASR, developed through the collaboration bewteen
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  [Asahi Ushio](https://asahiushio.com) and [Kotoba Technologies](https://twitter.com/kotoba_tech).
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  Following the original work of distil-whisper ([Robust Knowledge Distillation via Large-Scale Pseudo Labelling](https://arxiv.org/abs/2311.00430)),