website/_posts/research/2021-03-05-Vision_Transformer.md

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layout	title	categories	excerpt	header
single	Mel-Vision Transformer	research audio deep-learning anomalie-detection	Attention based audio classification on Mel-Spektrograms	teaser assets/figures/12_vision_transformer_teaser.jpg

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We apply the vision transformer, a deep machine learning model build around the attention mechanism, on mel-spectrogram representations of raw audio recordings. When adding mel-based data augmentation techniques and sample-weighting, we achieve comparable performance on both (PRS and CCS challenge) tasks of ComParE21, outperforming most single model baselines. We further introduce overlapping vertical patching and evaluate the influence of parameter configurations. {% cite illium2021visual %}

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