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Music, Mathematics and Language

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Produktnummer: 18d2fea32a9fd6450ab2cda0098eb2f719
Autor: Hamanaka, Masatoshi Hirata, Keiji Tojo, Satoshi
Themengebiete: artificial intelligence computational musicology mathematics in music music informatics semiotics
Veröffentlichungsdatum: 06.12.2022
EAN: 9789811951657
Sprache: Englisch
Seitenzahl: 257
Produktart: Gebunden
Verlag: Springer Singapore
Untertitel: The New Horizon of Computational Musicology Opened by Information Science
Produktinformationen "Music, Mathematics and Language"
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 onmusic information processing. In order to make the content as accessible as possible, each chapter is self-contained.
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