README.md

---
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.