Melodic segmentation: structure, cognition, algorithms

Název: Melodic segmentation: structure, cognition, algorithms
Zdrojový dokument: Musicologica Brunensia. 2017, roč. 52, č. 1, s. 53-61
Rozsah
53-61
  • ISSN
    1212-0391 (print)
    2336-436X (online)
Type: Článek
Jazyk
Licence: Neurčená licence
 

Upozornění: Tyto citace jsou generovány automaticky. Nemusí být zcela správně podle citačních pravidel.

Abstrakt(y)
Segmentation of melodies into smaller units (phrases, themes, motifs, etc.) is an important process in both music analysis and music cognition. Also, segmentation is a necessary preprocessing step for various tasks in music information retrieval. Several algorithms for automatic segmentation have been proposed, based on different music-theoretical backgrounds and computing approaches. Rule-based models operate on a given set of logical conditions. Learning-based models, originating in linguistics, compute segmentation criteria on the basis of statistical parameters of a training corpus and/or of the given composition. The aim of this preliminary study is to propose and describe a new segmentation algorithm that is rule-based, parsimonious, and unambiguous.
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