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Grouping compositions based on similarity of music themes.

ABSTRACT: 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.

SUBMITTER: Laskowska B

PROVIDER: S-EPMC7544027 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Grouping compositions based on similarity of music themes.

Laskowska Barbara B Kamola Mariusz M

PloS one 20201008 10

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 m ...[more]

PMID: 33031468

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Dataset Information

Grouping compositions based on similarity of music themes.

Publications

Grouping compositions based on similarity of music themes.

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