TY - JOUR
TI - Segmental pattern discovery in music
AU - Conklin, D.
AU - Anagnostopoulou, C.
JO - INFORMS Journal on Computing
PY - 2006
VL - 18
TODO - 3
SP - 285-293
PB - 
SN - 1091-9856, 1526-5528
TODO - 10.1287/ijoc.1040.0122
TODO - null
TODO - 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. © 2006 INFORMS.
ER -