readme: ---
  license: bsd-3-clause
  datasets:
  - speech_commands
  tags:
  - audio-classification
  model-index:
  - name: MIT/ast-finetuned-speech-commands-v2
    results:
    - task:
        type: audio-classification
      dataset:
        name: Speech Commands v2
        type: speech_commands
      metrics:
      - type: accuracy
        value: 98.12
  ---
  
  # Audio Spectrogram Transformer (fine-tuned on Speech Commands v2) 
  
  Audio Spectrogram Transformer (AST) model fine-tuned on Speech Commands v2. It was introduced in the paper [AST: Audio Spectrogram Transformer](https://arxiv.org/abs/2104.01778) by Gong et al. and first released in [this repository](https://github.com/YuanGongND/ast). 
  
  Disclaimer: The team releasing Audio Spectrogram Transformer did not write a model card for this model so this model card has been written by the Hugging Face team.
  
  ## Model description
  
  The Audio Spectrogram Transformer is equivalent to [ViT](https://huggingface.co/docs/transformers/model_doc/vit), but applied on audio. Audio is first turned into an image (as a spectrogram), after which a Vision Transformer is applied. The model gets state-of-the-art results on several audio classification benchmarks.
  
  ## Usage
  
  You can use the raw model for classifying audio into one of the Speech Commands v2 classes. See the [documentation](https://huggingface.co/docs/transformers/main/en/model_doc/audio-spectrogram-transformer) for more info.