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arXiv · 1906.08615

Zero-shot Learning and Knowledge Transfer in Music Classification and Tagging

Jeong Choi·Jongpil Lee·Jiyoung Park·Juhan Nam
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Abstract

Music classification and tagging is conducted through categorical supervised learning with a fixed set of labels. In principle, this cannot make predictions on unseen labels. Zero-shot learning is an approach to solve the problem by using side information about the semantic labels. We recently investigated this concept of zero-shot learning in music classification and tagging task by projecting both audio and label space on a single semantic space. In this work, we extend the work to verify the generalization ability of zero-shot learning model by conducting knowledge transfer to different music corpora.

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Jeong Choi, Jongpil Lee, Jiyoung Park, Juhan Nam. 2019-06-20. Zero-shot Learning and Knowledge Transfer in Music Classification and Tagging. https://arxiv.org/abs/1906.08615

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