Paper ID: 2206.04805

Motif Mining and Unsupervised Representation Learning for BirdCLEF 2022

Anthony Miyaguchi, Jiangyue Yu, Bryan Cheungvivatpant, Dakota Dudley, Aniketh Swain

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.

Submitted: Jun 8, 2022