The automated discovery of recurrent patterns in music is a fundamental task in computational music analysis. This paper describes a new method for discovering patterns in the vertical and horizontal dimensions of polyphonic music. A formal representation of music objects is used to structure the musical surface, and several ideas for viewing pieces as successions of vertical structures are examined. A knowledge representation method is used to view pieces as sequences of relationships between music objects, and a pattern discovery algorithm is applied using this view of the Bach chorale harmonizations to find significant recurrent patterns. The method finds a small set of vertical patterns that occur in a large number of pieces in the corpus. Most ofthese patterns represent specific voice leading formulae within cadences.
CITATION STYLE
Conklin, D. (2002). Representation and discovery of vertical patterns in music. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2445, pp. 32–42). Springer Verlag. https://doi.org/10.1007/3-540-45722-4_5
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