Computational Music Analysis

Research output: Book/ReportAnthologyResearchpeer-review

2 Citations (Scopus)

Abstract

This book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music.

The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns.

As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.
Original languageEnglish
Place of PublicationCham, Switzerland
PublisherSpringer
Edition1
Number of pages480
ISBN (Print)978-3-319-25929-1
ISBN (Electronic)978-3-319-25931-4
DOIs
Publication statusPublished - 2016

Fingerprint

Music
Music Information Retrieval
Pattern Discovery
Set Theory
Information Theory
Grammar
Information Retrieval
Pattern Recognition
Signal Processing
Machine Learning
Computer Science
Covering
Harmonic
Industry
Topology
Algebra
Resources
Range of data

Keywords

  • computational music analysis
  • music analysis
  • music information retrieval
  • mathematical music theory
  • music theory

Cite this

Meredith, David (Editor). / Computational Music Analysis. 1 ed. Cham, Switzerland : Springer, 2016. 480 p.
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Computational Music Analysis. / Meredith, David (Editor).

1 ed. Cham, Switzerland : Springer, 2016. 480 p.

Research output: Book/ReportAnthologyResearchpeer-review

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AB - This book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music.The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns.As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.

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