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Deep and Shallow

- Machine Learning in Music and Audio
Af: Shlomo Dubnov, Ross Greer Engelsk Paperback

Deep and Shallow

- Machine Learning in Music and Audio
Af: Shlomo Dubnov, Ross Greer Engelsk Paperback
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Providing an essential and unique bridge between the theories of signal processing, machine learning, and artificial intelligence (AI) in music, this book provides a holistic overview of foundational ideas in music, from the physical and mathematical properties of sound to symbolic representations. Combining signals and language models in one place, this book explores how sound may be represented and manipulated by computer systems, and how our devices may come to recognize particular sonic patterns as musically meaningful or creative through the lens of information theory.

Introducing popular fundamental ideas in AI at a comfortable pace, more complex discussions around implementations and implications in musical creativity are gradually incorporated as the book progresses. Each chapter is accompanied by guided programming activities designed to familiarize readers with practical implications of discussed theory, without the frustrations of free-form coding.

Surveying state-of-the art methods in applications of deep neural networks to audio and sound computing, as well as offering a research perspective that suggests future challenges in music and AI research, this book appeals to both students of AI and music, as well as industry professionals in the fields of machine learning, music, and AI.

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Providing an essential and unique bridge between the theories of signal processing, machine learning, and artificial intelligence (AI) in music, this book provides a holistic overview of foundational ideas in music, from the physical and mathematical properties of sound to symbolic representations. Combining signals and language models in one place, this book explores how sound may be represented and manipulated by computer systems, and how our devices may come to recognize particular sonic patterns as musically meaningful or creative through the lens of information theory.

Introducing popular fundamental ideas in AI at a comfortable pace, more complex discussions around implementations and implications in musical creativity are gradually incorporated as the book progresses. Each chapter is accompanied by guided programming activities designed to familiarize readers with practical implications of discussed theory, without the frustrations of free-form coding.

Surveying state-of-the art methods in applications of deep neural networks to audio and sound computing, as well as offering a research perspective that suggests future challenges in music and AI research, this book appeals to both students of AI and music, as well as industry professionals in the fields of machine learning, music, and AI.

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Produktdetaljer
Sprog: Engelsk
Sider: 328
ISBN-13: 9781032133911
Indbinding: Paperback
Udgave:
ISBN-10: 1032133910
Kategori: Automatisk styrings- & reguleringsteknik
Udg. Dato: 8 dec 2023
Længde: 23mm
Bredde: 235mm
Højde: 156mm
Forlag: Taylor & Francis Ltd
Oplagsdato: 8 dec 2023
Forfatter(e): Shlomo Dubnov, Ross Greer
Forfatter(e) Shlomo Dubnov, Ross Greer

Kategori Automatisk styrings- & reguleringsteknik

ISBN-13 9781032133911

Sprog Engelsk

Indbinding Paperback

Sider 328

Udgave

Længde 23mm

Bredde 235mm

Højde 156mm

Udg. Dato 8 dec 2023

Oplagsdato 8 dec 2023

Forlag Taylor & Francis Ltd