Handbook of Artificial Intelligence for Music
Description
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.
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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 G uide to Computing for Expressive Music Performance .
Content
.- Artificial Intelligence in Music and Performance: A Subjective Art-Research Inquiry.
.- Performance Creativity in Computer Systems for Expressive Performance of Music.
.- Interactive Machine Learning of Musical Gesture.
.- Automatic Music Composition with Evolutionary Algorithms: Digging into the Roots of Biological Creativity.
.- Human-Robot Musical Interaction.
.- Shimon Sings-Robotic Musicianship Finds Its Voice.
.- AI-Lectronica: Music AI in Clubs and Studio Production.
.- Instruments of the Unexpected: Designing AI Music Tools and Systems for Creative Misappropriation.
.- The Intrusion of the Machinic on the Human: Musical Deconstructivism Through a Case Study of The Cherry Orchard Opera.
.- On Making Music with Heartbeats.
.- JHAIMI: Joint Human AI Music Improviser.
.- Neuroscience of Musical Improvisation.
.- Discovering the Neuroanatomical Correlates of Music with Machine Learning.
.- Music, Artificial Intelligence and Neuroscience.
.- Creative Music Neurotechnology.
.- cellF: Surrogate Musicianship as a Manifestation of In-Vitro Intelligence.
.- On Growing Computers from Living Biological Cells.
.- Quantum Computer: Hello, Music!.
.- Non-Classical Generative Music: Exploring Quantum Procedural Generation through Cellular Automata.