Deep and shallow machine learning in music and audio / Shlomo Dubnov and Ross Greer.
| Author/creator | Dubnov, Shlomo |
| Other author | Greer, Ross. |
| Format | Electronic |
| Edition | First edition. |
| Publication Info | Boca Raton : CRC Press, 2024. |
| Description | xvi, 328 pages : illustrations, music ; 24 cm. |
| Supplemental Content | Full text available from eBooks on EBSCOhost |
| Subjects |
| Series | CRC machine learning & pattern recognition |
| Contents | Introduction to Sounds of Music -- Noise : the Hidden Dynamics of Music -- Communicating Musical Information -- Understanding and (Re)Creating Sound -- Generating and Listening to Audio Information -- Artificial Musical Brains -- Representing Voices in Pitch and Time -- Noise Revisited : Brains that Imagine -- Paying (Musical) Attention -- 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. |
| Abstract | "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 familiarise 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"-- Provided by publisher. |
| Bibliography note | Includes bibliographical references (305-316) and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2023019698 |
| ISBN | 9781032146188 (hardback) |
| ISBN | 9781032133911 (paperback) |
| ISBN | (ebook) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |