Mixture of Mixups for Multi-label Classification of Rare Anuran Sounds

arXiv:2403.09598v1 Announce Type: cross
Abstract: Multi-label imbalanced classification poses a significant challenge in machine learning, particularly evident in bioacoustics where animal sounds often co-occur, and certain sounds are much less frequent than others. This paper focuses on the specific case of classifying anuran species sounds using the dataset AnuraSet, that contains both class imbalance and multi-label examples. To address these challenges, we introduce Mixture of Mixups (Mix2), a framework that leverages mixing regularization methods Mixup, Manifold Mixup, and MultiMix. Experimental …

abstract arxiv case challenge classification cs.lg cs.sd dataset eess.as machine machine learning paper species type