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arXiv · 1612.05070

Towards End-to-End Audio-Sheet-Music Retrieval

Matthias Dorfer·Andreas Arzt·Gerhard Widmer
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Abstract

This paper demonstrates the feasibility of learning to retrieve short snippets of sheet music (images) when given a short query excerpt of music (audio) -- and vice versa --, without any symbolic representation of music or scores. This would be highly useful in many content-based musical retrieval scenarios. Our approach is based on Deep Canonical Correlation Analysis (DCCA) and learns correlated latent spaces allowing for cross-modality retrieval in both directions. Initial experiments with relatively simple monophonic music show promising results.

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BibTeXRIS

Matthias Dorfer, Andreas Arzt, Gerhard Widmer. 2016-12-15. Towards End-to-End Audio-Sheet-Music Retrieval. https://arxiv.org/abs/1612.05070

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