Music, mathematics and language : the new horizon of computational musicology opened by information science / Keiji Hirata, Satoshi Tojo, Masatoshi Hamanaka.
Hirata, Keiji, author.; Tojo, Satoshi, author.; Hamanaka, Masatoshi, author.
2022
ML74
Available Online

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Title Music, mathematics and language : the new horizon of computational musicology opened by information science / Keiji Hirata, Satoshi Tojo, Masatoshi Hamanaka.
Author Hirata, Keiji, author.
ISBN 9789811951664 (electronic bk.)
9811951667 (electronic bk.)
9789811951657
9811951659
DOI https://doi.org/10.1007/978-981-19-5166-4
Published Singapore : Springer, [2022]
Copyright ©2022
Language English
Description 1 online resource (xiv, 257 pages) : illustrations (some color)
Item Number 10.1007/978-981-19-5166-4 doi
Call Number ML74
Dewey Decimal Classification 780.285
Summary This book presents a new approach to computational musicology in which music becomes a computational entity based on human cognition, allowing us to calculate music like numbers. Does music have semantics? Can the meaning of music be revealed using symbols and described using language? The authors seek to answer these questions in order to reveal the essence of music. Chapter 1 addresses a very fundamental point, the meaning of music, while referring to semiotics, gestalt, Schenkerian analysis and cognitive reality. Chapter 2 considers why the 12-tone equal temperament came to be prevalent. This chapter serves as an introduction to the mathematical definition of harmony, which concerns the ratios of frequency in tonic waves. Chapter 3, "Music and Language", explains the fundamentals of grammar theory and the compositionality principle, which states that the semantics of a sentence can be composed in parallel to its syntactic structure. In turn, Chapter 4 explains the most prevalent score notation the Berklee method, which originated at the Berklee School of Music in Boston from a different point of view, namely, symbolic computation based on music theory. Chapters 5 and 6 introduce readers to two important theories, the implication-realization model and generative theory of tonal music (GTTM), and explain the essence of these theories, also from a computational standpoint. The authors seek to reinterpret these theories, aiming at their formalization and implementation on a computer. Chapter 7 presents the outcomes of this attempt, describing the framework that the authors have developed, in which music is formalized and becomes computable. Chapters 8 and 9 are devoted to GTTM analyzers and the applications of GTTM. Lastly, Chapter 10 discusses the future of music in connection with computation and artificial intelligence. This book is intended both for general readers who are interested in music, and scientists whose research focuses on music information processing. In order to make the content as accessible as possible, each chapter is self-contained.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed December 29, 2022).
Added Author Tojo, Satoshi, author.
Hamanaka, Masatoshi, author.
Available in Other Form Print version: 9789811951657
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Chapter 1: Toward the Machine Computing Semantics of Music
Chapter 2: Mathematics of Temperament: Principle and Development
Chapter 3: Music and Natural Language
Chapter 4: Berklee Method
Chapter 5: Implication-Realization Model
Chapter 6: Generative Theory of Tonal Music and Tonal Pitch Space
Chapter 7: Formalization of GTTM
Chapter 8: Implementation of GTTM
Chapter 9: Application of GTTM
Chapter 10: Epilogue.

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