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Communication Dans Un Congrès Année : 2023

Adding descriptors to melodies improves pattern matching: a study on Slovenian folk songs

Résumé

Pattern matching is a widely spread topic in MIR and related fields. It commonly aims to provide insights into repetitive instances in or across different kinds of music or cultures. The paper presents a study on the analysis of folksongs using symbolic music representation, including both music content and its contextual information. We release a corpus of 400 monophonic Slovenian tunes with structure, contour, and implied harmony annotations. We show that certain descriptors, such as contour types and harmonic ``stability'', depend on phrase position in tune. We propose a time and space-efficient algorithm based on suffix arrays and bit-vectors to match both music content (melodic sequence) and music context (descriptors). We show that pattern-matching queries combining melody and descriptors are more precise for classification tasks. We emphasize the importance of collaborative dynamics between content and context, as well as stress that not all research questions require the same amount of details. Consequently, our approach is encouraging computational music analysis to become more flexible. Lastly, the study aims to promote knowledge of Slovenian folksong.
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Dates et versions

hal-04142315 , version 1 (03-11-2023)

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Vanessa Nina Borsan, Mathieu Giraud, Richard Groult, Thierry Lecroq. Adding descriptors to melodies improves pattern matching: a study on Slovenian folk songs. International Society for Music Information Retrieval Conference (ISMIR 2023), 2023, Milan, Italy. pp.474-481, ⟨10.5281/zenodo.10265328⟩. ⟨hal-04142315⟩
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