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metadata
datasets:
  - agkphysics/AudioSet
  - openslr/librispeech_asr
pipeline_tag: audio-classification
license: bsd-3-clause
tags:
  - audio-classification

Self Supervised Audio Spectrogram Transformer (pretrained on AudioSet/Librispeech)

Self Supervised Audio Spectrogram Transformer (SSAST) model with uninitialized classifier head. It was introduced in the paper SSAST: Self-Supervised Audio Spectrogram Transformer by Gong et al. and first released in this repository.

Disclaimer: The team releasing Audio Spectrogram Transformer did not write a model card for this model.

Model description

The Audio Spectrogram Transformer is equivalent to 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

The model is pretrained on a massive amount of audio. Please finetune the classifier head before use, as it comes uninitialized.