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Grouping compositions based on similarity of music themes
Author(s) -
Barbara Laskowska,
Mariusz Кamola
Publication year - 2020
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0240443
Subject(s) - similarity (geometry) , computational biology , computer science , biology , artificial intelligence , image (mathematics)
Finding music pieces whose similarity is explainable in plain musical terms can be of considerable value in many applications. We propose a composition grouping method based on musicological approach. The underlying idea is to compare music notation to natural language. In music notation, a musical theme corresponds to a word. The more similar motives we find in two musical pieces, the higher is their overall similarity score. We develop the definition of a motive as well as the way to compare motives and whole compositions. To verify our framework we conduct a number of grouping and classification experiments for typical musical corpora. They include works by classical composers and examples of folk music. Obtained results are encouraging; the method is able to find non-obvious similarities, yet its operation remains explicable on the ground of music history. The proposed approach can be used in music recommendation and anti-plagiarism systems. Due to the musicological flavor, one of potentially best applications of our method would be that in computer assisted music analysis tools.

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