Motif Mining and Unsupervised Representation Learning for BirdCLEF 2022
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2022
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| Subjects: | |
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| _version_ | 1866913421373472768 |
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| author | Miyaguchi, Anthony Yu, Jiangyue Cheungvivatpant, Bryan Dudley, Dakota Swain, Aniketh |
| author_facet | Miyaguchi, Anthony Yu, Jiangyue Cheungvivatpant, Bryan Dudley, Dakota Swain, Aniketh |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2206_04805 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Motif Mining and Unsupervised Representation Learning for BirdCLEF 2022 Miyaguchi, Anthony Yu, Jiangyue Cheungvivatpant, Bryan Dudley, Dakota Swain, Aniketh Sound Machine Learning Audio and Speech Processing 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. |
| title | Motif Mining and Unsupervised Representation Learning for BirdCLEF 2022 |
| topic | Sound Machine Learning Audio and Speech Processing |
| url | https://arxiv.org/abs/2206.04805 |