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Visual Transformers for Primates Classification and Covid Detection

2022-12-20 09:10:25
Steffen Illium, Robert Müller, Andreas Sedlmeier, Claudia-Linnhoff Popien

Abstract

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. Index Terms: audio classification, attention, mel-spectrogram, unbalanced data-sets, computational paralinguistics

Abstract (translated)

URL

https://arxiv.org/abs/2212.10093

PDF

https://arxiv.org/pdf/2212.10093.pdf


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