國立虎尾科技大學 |

Computational music analysis

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Computational music analysis/ edited by David Meredith.
other author:	Meredith, David.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	xv, 480 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Music - Mathematics. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-25931-4
ISBN:	9783319259314

Computational music analysis
Computational music analysis[electronic resource] /edited by David Meredith. - Cham :Springer International Publishing :2016. - xv, 480 p. :ill., digital ;24 cm.

Music Analysis by Computer Ontology and Epistemology -- The Harmonic Musical Surface and Two Novel Chord Representation Schemes -- Topological Structures in Computer-Aided Music Analysis -- Contextual Set-Class Analysis -- Computational Analysis of Musical Form -- Chord- and Note-Based Approaches to Voice Separation -- Analysing Symbolic Music with Probabilistic Grammars -- Interactive Melodic Analysis -- Implementing Methods for Analysing Music Based on Lerdahl and Jackendoff's Generative Theory of Tonal Music -- An Algebraic Approach to Time-Span Reduction -- Automated Motivic Analysis An Exhaustive Approach Based on Closed and Cyclic Pattern Mining in Multidimensional Parametric Spaces -- A Wavelet-Based Approach to Pattern Discovery in Melodies -- Analysing Music with Point-Set Compression Algorithms -- Composer Classification Models for Music-Theory Building -- Contrast Pattern Mining in Folk Music Analysis -- Pattern and Antipattern Discovery in Ethiopian Bagana Songs -- Using Geometric Symbolic Fingerprinting to Discover Distinctive Patterns in Polyphonic Music Corpora -- Index.

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.

ISBN: 9783319259314

Standard No.: 10.1007/978-3-319-25931-4doiSubjects--Topical Terms:

1102253
Music
--Mathematics.

LC Class. No.: ML3800 / .C66 2016

Dewey Class. No.: 780.1

Computational music analysis
LDR:03577nam a2200337 a 4500 001 860546
003 DE-He213
005 20160725151643.0
006 m d
007 cr nn 008maaau
008 170720s2016 gw s 0 eng d
020 $a 9783319259314 $q (electronic bk.)
020 $a 9783319259291 $q (paper)
024 7 $a 10.1007/978-3-319-25931-4 $2 doi
035 $a 978-3-319-25931-4
040 $a GP $c GP
041 0 $a eng
050 4 $a ML3800 $b .C66 2016
072 7 $a H $2 bicssc
072 7 $a UB $2 bicssc
072 7 $a COM018000 $2 bisacsh
072 7 $a ART000000 $2 bisacsh
082 0 4 $a 780.1 $2 23
090 $a ML3800 $b .C738 2016
245 0 0 $a Computational music analysis $h [electronic resource] / $c edited by David Meredith.
260 $a Cham : $c 2016. $b Springer International Publishing : $b Imprint: Springer,
300 $a xv, 480 p. : $b ill., digital ; $c 24 cm.
505 0 $a Music Analysis by Computer Ontology and Epistemology -- The Harmonic Musical Surface and Two Novel Chord Representation Schemes -- Topological Structures in Computer-Aided Music Analysis -- Contextual Set-Class Analysis -- Computational Analysis of Musical Form -- Chord- and Note-Based Approaches to Voice Separation -- Analysing Symbolic Music with Probabilistic Grammars -- Interactive Melodic Analysis -- Implementing Methods for Analysing Music Based on Lerdahl and Jackendoff's Generative Theory of Tonal Music -- An Algebraic Approach to Time-Span Reduction -- Automated Motivic Analysis An Exhaustive Approach Based on Closed and Cyclic Pattern Mining in Multidimensional Parametric Spaces -- A Wavelet-Based Approach to Pattern Discovery in Melodies -- Analysing Music with Point-Set Compression Algorithms -- Composer Classification Models for Music-Theory Building -- Contrast Pattern Mining in Folk Music Analysis -- Pattern and Antipattern Discovery in Ethiopian Bagana Songs -- Using Geometric Symbolic Fingerprinting to Discover Distinctive Patterns in Polyphonic Music Corpora -- Index.
520 $a 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.
650 0 $a Music $x Mathematics. $3 1102253
650 0 $a Musical analysis. $3 560038
650 1 4 $a Computer Science. $3 593922
650 2 4 $a Computer Appl. in Arts and Humanities. $3 669937
650 2 4 $a Music. $3 649088
700 1 $a Meredith, David. $3 1102252
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-25931-4
950 $a Computer Science (Springer-11645)