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arXiv · 2206.04805

Motif Mining and Unsupervised Representation Learning for BirdCLEF 2022

Anthony Miyaguchi·Jiangyue Yu·Bryan Cheungvivatpant·Dakota Dudley·Aniketh Swain
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Abstract

We build a classification model for the BirdCLEF 2022 challenge using unsupervised methods. We implement an unsupervised representation of the training dataset using a triplet loss on spectrogram representation of audio motifs. Our best model performs with a score of 0.48 on the public leaderboard.

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Anthony Miyaguchi, Jiangyue Yu, Bryan Cheungvivatpant, Dakota Dudley, Aniketh Swain. 2022-06-08. Motif Mining and Unsupervised Representation Learning for BirdCLEF 2022. https://arxiv.org/abs/2206.04805

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