Computational music analysis. (English) Zbl 1369.00103

Cham: Springer (ISBN 978-3-319-25929-1/hbk; 978-3-319-25931-4/ebook). xv, 480 p. (2016).

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Publisher’s description: 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.
The articles of mathematical interest will be reviewed individually.
Indexed articles:
Marsden, Alan, Music analysis by computer: ontology and epistemology, 3-28 [Zbl 1375.00077]
Cambouropoulos, Emilios, The harmonic musical surface and two novel chord representation schemes, 31-56 [Zbl 1375.00068]
Bigo, Louis; Andreatta, Moreno, Topological structures in computer-aided music analysis, 57-80 [Zbl 1375.00067]
Martorell, Agustín; Gómez, Emilia, Contextual set-class analysis, 81-110 [Zbl 1375.00078]
Giraud, Mathieu; Groult, Richard; Levé, Florence, Computational analysis of musical form, 113-136 [Zbl 1375.00071]
Weyde, Tillman; de Valk, Reinier, Chord- and note-based approaches to voice separation, 137-154 [Zbl 1375.00084]
Abdallah, Samer; Gold, Nicolas; Marsden, Alan, Analysing symbolic music with probabilistic grammars, 157-189 [Zbl 1375.00065]
Rizo, David; Illescas, Plácido R.; Iñesta, José M., Interactive melodic analysis, 191-219 [Zbl 1375.00082]
Hamanaka, Masatoshi; Hirata, Keiji; Tojo, Satoshi, Implementing methods for analysing music based on Lerdahl and Jackendoff’s Generative Theory of Tonal Music, 221-249 [Zbl 1375.00072]
Hirata, Keiji; Tojo, Satoshi; Hamanaka, Masatoshi, An algebraic approach to time-span reduction, 251-270 [Zbl 1375.00074]
Lartillot, Olivier, Automated motivic analysis: an exhaustive approach based on closed and cyclic pattern mining in multidimensional parametric spaces, 273-302 [Zbl 1375.00076]
Velarde, Gissel; Meredith, David; Weyde, Tillman, A wavelet-based approach to pattern discovery in melodies, 303-333 [Zbl 1375.00083]
Meredith, David, Analysing music with point-set compression algorithms, 335-366 [Zbl 1375.00079]
Herremans, Dorien; Martens, David; Sörensen, Kenneth, Composer classification models for music-theory building, 369-392 [Zbl 1375.00073]
Neubarth, Kerstin; Conklin, Darrell, Contrast pattern mining in folk music analysis, 393-424 [Zbl 1375.00080]
Conklin, Darrell; Weisser, Stéphanie, Pattern and antipattern discovery in Ethiopian bagana songs, 425-443 [Zbl 1375.00070]
Collins, Tom; Arzt, Andreas; Frostel, Harald; Widmer, Gerhard, Using geometric symbolic fingerprinting to discover distinctive patterns in polyphonic music corpora, 445-474 [Zbl 1375.00069]

MSC:

00B15	Collections of articles of miscellaneous specific interest
00A65	Mathematics and music
00A69	General applied mathematics