Handbook of Artificial Intelligence for Music

This book presents comprehensive coverage of the latest advances in research into enabling machines to listen to and compose new music. It includes chapters introducing what we know about human musical intelligence and on how this knowledge can be simulated with AI. The development of interactive musical robots and emerging new approaches to AI-based musical creativity are also introduced, including braincomputer music interfaces, bio-processors and quantum computing.
Artificial Intelligence (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 book focuses on a largely unexplored application: AI for creating the actual musical content.

The definitive work on AI and music computing, featuring insights from leading experts 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

Autorentext

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.

Inhalt
Preface.- Foreword.- A Sociocultural and Design Perspectives on AI-based Music Production:Why do we make music what changes if AI makes it for us?.- Human-Machine Simultaneity in the Compositional Process.- Artificial Intelligence for Music Composition.- Artificial Intelligence in Music and Performance: A subjective art-research inquiry.- Neuroscience of Musical Improvisation.,- Discovering the Neuroanatomical Correlates of Music with Machine Learning.- Music, Artificial Intelligence and Neuroscience.- Creative Music Neurotechnology.- On Making Music with Heartbeats.- Cognitive Musicology and Artificial Intelligence: Harmonic Analysis, Learning and Generation.- On Modelling Harmony with Constraint Programming for Algorithmic Composition Including a Model of Schoenberg's Theory of Harmony.- Constraint-Solving System in Music Creation.- AI Music Mixing Systems.- Machine Improvisation in Music: Information theoretic approach.- Structure, Abstraction and Reference in Artificial Musical Intelligence.- Folk the Algorithms: (Mis)Applying Artificial Intelligence to Folk Music.- Automatic Music Composition with Evolutionary Algorithms: Digging into the roots of biological creativity.- Assisted Music Creation with Flow Machines: Towards new categories of new.- Performance Creativity in Computer Systems for Expressive Performance of Music.- Imitative Computer-Aided Musical Orchestration with Biologically Inspired Algorithms.- Human-centred Artificial Intelligence in Concatenative Sound Synthesis.- Deep Generative Models for Musical Audio Synthesis.- Transfer Learning for Generalized Audio Signal Processing.- From Audio to Music Notation.- Automatic Transcription of Polyphonic Vocal Music.- Graph-Based Representation, Analysis and Interpretation of Popular Music Lyrics Using Semantic Embedding Features.- Interactive Machine Learning of Musical Gesture.- Human-Robot Musical Interaction.- Shimon Sings: Robotic musicianship finds its voice.- AI-lectronica: Music AI in clubs and studio production.- Musicking with Algorithms: Thoughts on Artificial Intelligence, Creativity and Agency.- cellF: Surrogate Musicianship as Manifestation of In-vitro Intelligence.- On Growing Computers from Living Biological Cells: Let's take a walk on the wild side of Artificial Intelligence.- Quantum Computer: Hello Music.