
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
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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Information
Table of contents
- Cover Page
- Endorsements Page
- Half-Title Page
- Series Page
- Title Page
- Copyright Page
- Dedication Page
- Contents
- Preface
- Chapter 1 Introduction to Sounds of Music
- Chapter 2 Noise: The Hidden Dynamics of Music
- Chapter 3 Communicating Musical Information
- Chapter 4 Understanding and (Re)Creating Sound
- Chapter 5 Generating and Listening to Audio Information
- Chapter 6 Artificial Musical Brains
- Chapter 7 Representing Voices in Pitch and Time
- Chapter 8 Noise Revisited: Brains that Imagine
- Chapter 9 Paying (Musical) Attention
- Chapter 10 Last Noisy Thoughts, Summary, and Conclusion
- Appendix A Introduction to Neural Network Frameworks: Keras, Tensorflow, Pytorch
- Appendix B Summary of Programming Examples and Exercises
- Appendix C Software Packages for Music and Audio Representation and Analysis
- Appendix D Free Music and Audio-Editing Software
- Appendix E Datasets
- Appendix F Figure Attributions
- References
- Index