Pattern in Music

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Annotation Datasets
Arab Andalusian Music
Category=AVA
Category=PBK
Category=UY
Chord Classes
Chord Types
Closed Patterns
computational analysis
computational musicology
corpus-based musicology
Data Sets
eq_art-fashion-photography
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_music
eq_nobargain
eq_non-fiction
Fuzzy Patterns
inductive pattern discovery in music
Inter-annotator Agreement
Interval Class Vectors
Kernel Density Estimation Function
mathematical music theory
mathematics and music
melodic contour mining
Mirex
music analysis
music pattern recognition
music theory
Note Pairs
Pattern Discovery
Pattern Discovery Algorithms
Period Extraction
polyphonic structure analysis
Positive Corpus
Range Query
Reference Patterns
Sequential Pattern Mining
Seventh Chords
Sound And Music Computing
Target Class
Tonal Progressions
Turkish Makam Music
Young Men

Product details

  • ISBN 9781032600949
  • Weight: 453g
  • Dimensions: 174 x 246mm
  • Publication Date: 14 Nov 2023
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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This book presents analyses of pattern in music from different computational and mathematical perspectives.

A central purpose of music analysis is to represent, discover, and evaluate repeated structures within single pieces or within larger corpora of related pieces. In the chapters of this book, music corpora are structured as monophonic melodies, polyphony, or chord sequences. Patterns are represented either extensionally as locations of pattern occurrences in the music, or intensionally as sequences of pitch or chord features, rhythmic profiles, geometric point sets, and logical expressions. 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. Results are evaluated using a variety of methods including visualization, contrasting corpus analysis, and reference to known and expected patterns.

Pattern in Music will be a key resource for academics, researchers, and advanced students of music, musicology, music analyses, mathematical music theory, computational musicology, and music informatics. This book was originally published as a special issue of the Journal of Mathematics and Music.

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.