Pattern in Music

This book presents analyses of pattern in music from different computational and mathematical perspectives.The chapters cover both deductive analysis, where music is queried for occurrences of a known pattern, and inductive analysis, where patterns are found using pattern discovery algorithms.

Darrell Conklin is an Ikerbasque Research Professor in the Department of Computer Science and Artificial Intelligence at the University of the Basque Country, San Sebastian, Spain.

Introduction: Pattern in music 1. Discovering distorted repeating patterns in polyphonic music through longest increasing subsequences 2. Mining contour sequences for significant closed patterns 3. Parsimonious graphs for the most common trichords and tetrachords 4. Triadic patterns across classical and popular music corpora: stylistic conventions, or characteristic idioms? 5. Modelling pattern interestingness in comparative music corpus analysis 6. A computational exploration of melodic patterns in Arab-Andalusian music 7. Some observations on autocorrelated patterns within computational meter identification 8. Exploring annotations for musical pattern discovery gathered with digital annotation tools