AI technology permeates the music industry, from management systems for recording studios to recommendation systems for online commercialization of music through the Internet. Yet whereas AI for online music distribution is well advanced, this unique handbook focuses on a largely unexplored application:  AI for creating the actual musical content. 

Significantly, the two-volume reference presents comprehensive coverage of the latest advances in research into enabling machines to listen to and compose new music.

The first volume, Fundamentals and Theory, essentially covers basic research, theoretical approaches and applications of AI in signal processing. The second volume, Approaches and Practices, focuses on applications of AI in musical composition, performance and robotics. Emerging new approaches to AI-based musical creativity also are introduced, including brain–computer music interfaces, bio-processors and quantum computing. 

Topics and features:

* Presents the definitive work on AI and music computing, featuring insights from leading experts and practitioners in the field

* Highlights how AI is much more than just deep learning, showcasing a range of different approaches and developments

* Introduces new and emerging topics in AI, including biocomputing and quantum computing

Prof. Eduardo Reck Miranda is a composer and professor in Computer Music at the University of Plymouth, UK, where he is director of the Interdisciplinary Centre for Computer Music Research. His previous publications include the Springer titles Guide to Unconventional Computing for Music, Guide to Brain-Computer Music Interfacing and Guide to Computing for Expressive Music Performance.

Prof. Eduardo Reck Miranda is a composer and Professor in Computer Music at the University of Plymouth, UK, where he is Director of the Interdisciplinary Centre for Computer Music Research (ICCMR). His previous publications include the Springer titles Guide to Unconventional Computing for Music, Guide to Brain-Computer Music Interfacing and Guide to Computing for Expressive Music Performance.