Scaling and compressing melodies using geometric similarity measures

L.E. Caraballo, J.M. Díaz-Báñez, F. Rodríguez, V. Sánchez-Canales and I. Ventura

Applied Mathematics and Computation, 2022, vol. 426, issue C

Abstract: Melodic similarity measurement is of key importance in music information retrieval. In this paper, we use geometric matching techniques to measure the similarity between two melodies. We represent music as sets of points or sets of horizontal line segments in the Euclidean plane and propose efficient algorithms for optimization problems inspired in two operations on melodies; linear scaling and audio compression. In the scaling problem, an incoming query melody is scaled forward until the similarity measure between the query and a reference melody is minimized. The compression problem asks for a subset of notes of a given melody such that the matching cost between the selected notes and the reference melody is minimized.

Keywords: Melodic similarity; Geometric; Matching; Algorithm; Scaling; Compressing (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:426:y:2022:i:c:s0096300322002144

DOI: 10.1016/j.amc.2022.127130

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