readme: ---
  language:
  - ja  
  license: apache-2.0
  tags:
  - audio
  - automatic-speech-recognition
  - speech
  datasets:
  - Japanese accent datasets
  metrics:
  - wer
  
  # Optional. Add this if you want to encode your eval results in a structured way.
  model-index:
  - name: Wav2vec2 Accent Japanese
    results:
    - task: 
        type: Speech Recognition  # Required. Example: automatic-speech-recognition
        name: automatic-speech-recognition  # Optional. Example: Speech Recognition
      dataset:
        type: accent_voice  
        name: Japanese accent datasets 
        args: ja         
      metrics:
        - type: wer   # Required. 
          value: 15.82   # Required.
          name: Test WER            
  ---
  # Wav2Vec2 Accent Japanese
  Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Japanese accent dataset 
  When using this model, make sure that your speech input is sampled at 16kHz.
  
  ## Test Result
  WER: 15.82%  