Motif Mining and Unsupervised Representation Learning for BirdCLEF 2022

06/08/2022

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by   Anthony Miyaguchi, et al.

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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.