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001			394536
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005			20230102123139.0
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008			221205s2022 si | s |||| 0|eng d
020			_a9789811951664
024	7		_a10.1007/978-981-19-5166-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
100	1		_aHirata, Keiji _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aMusic, Mathematics and Language _bThe New Horizon of Computational Musicology Opened by Information Science _cby Keiji Hirata, Satoshi Tojo, Masatoshi Hamanaka
250			_a1st edition 2022
264		1	_aSingapore _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XIV, 257 páginas) _b149 ilustraciones, 29 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
505	0		_aChapter 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.
520			_aThis 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.
700	1		_aTojo, Satoshi _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aHamanaka, Masatoshi _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iPrinted edition: _z9789811951657
776	0	8	_iPrinted edition: _z9789811951671
776	0	8	_iPrinted edition: _z9789811951688
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-19-5166-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_Computer_2022
999			_c394536 _d394536