Segmental pattern discovery in music

Segmental pattern discovery in music

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Article ID: iaor20071069
Country: United States
Volume: 18
Issue: 3
Start Page Number: 285
End Page Number: 293
Publication Date: Jun 2006
Journal: INFORMS Journal On Computing
Authors: ,
Keywords: music
Abstract:

In this paper we describe a new method for discovering recurrent patterns in a corpus of segmented melodies. Elements of patterns in this scheme do not represent individual notes but rather represent melodic segments that are sequences of notes. A new knowledge representation for segmental patterns is designed, and a pattern discovery algorithm based on suffix trees is used to discover segmental patterns in large corpora. The method is applied to a large collection of melodies, including Nova Scotia folk songs, Bach chorale melodies, and sections from the Essen folk song database. Patterns are ranked using a statistical significance method that integrates pattern self-overlap, length, and frequency in a corpus into a single measure. A musical interpretation of some of the statistically significant discovered patterns is presented.

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