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--- |
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license: bsd-3-clause |
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datasets: |
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- speech_commands |
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tags: |
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- audio-classification |
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model-index: |
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- name: MIT/ast-finetuned-speech-commands-v2 |
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results: |
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- task: |
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type: audio-classification |
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dataset: |
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name: Speech Commands v2 |
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type: speech_commands |
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metrics: |
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- type: accuracy |
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value: 98.12 |
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--- |
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# Audio Spectrogram Transformer (fine-tuned on Speech Commands v2) |
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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). |
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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. |
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## Model description |
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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. |
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## Usage |
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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. |
