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Towards End-to-End Audio-Sheet-Music Retrieval (1612.05070v1)
Published 15 Dec 2016 in cs.SD, cs.IR, and cs.LG
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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