Melodic segmentation: structure, cognition, algorithms

Title: Melodic segmentation: structure, cognition, algorithms
Source document: Musicologica Brunensia. 2017, vol. 52, iss. 1, pp. 53-61
Extent
53-61
  • ISSN
    1212-0391 (print)
    2336-436X (online)
Type: Article
Language
License: Not specified license
 

Notice: These citations are automatically created and might not follow citation rules properly.

Abstract(s)
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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