Handbook of Artificial Intelligence for Music: Foundations, Advanced Approaches, and Developments for Creativity

ISBN-13: 9783030721183 / Angielski / Miękka / 2022

Miranda, Eduardo Reck

Opis

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 brain–computer 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.

Spis treści

Part I: Understanding Musical Intelligence

Cognitive Neuroscience of Music
Stefan Koelsh

The Musical Brain
Aniruddh Patel

The Neuroscience of Musical Improvisation
Psyche Loui

Part II: Machine Perception and Analysis

Machine Listening of Music
Juan Pablo Bello

Convolutional Neural Networks for Audio Spectrogram Representation
Lonce Wyse

Robot Musicianship
Gil Weinberg

Robot Understanding of Conductor Gestures
Atsuo Takahishi

Human-Robot Emotional Musical Interaction
Massimiliano Zecca

Machine Recognition of Musical Emotion
Yi-Hsuan Yang and Homer H. Chen

Optical Recognition of Music Notation
Ana Bebelo

Music Transcription: from Audio to Music Notation
Emmanouil Benetos

Machine Learning System for Harmonic Analysis of Music
Tijl De Bie

Machine Learning of Jazz
Jon Gillick

Artificial Intelligence Data Mining for Music
Tao Li

Machine Learning of Body Movement in Instrumental Music Performance
Federico Visi

Machine Learning of Orchestral Conductor’s Baton Movements
Donald G. Dansereau

Machine Recognition of Music Emotion
Yi-Hsuan Yang and Homer H. Chen

Part III: Machine Composing and Performance

Flow Machines
Francois Pachet

Machine Improvisation
Shlomo Dubnov

Artificial Agents for Collaborative Free Improvisation
Adam Linson

Symbolic Computational Creativity
David Cope

Tracing the Compositional Process
Hanns Holger Rutz

Composing with Intelligent Interactive Musical Agents
Marcelo Gimenes

Creating Music Autonomously with Evolutionary Algorithms
Francisco J. Vico

Constraint-Solving System for Generating Music Scores
Orjan Sandred

Constraint Modeling of Music Theories
Torsten Anders

Machine Learning Algorithm for Musical Composition
Rebecca Fierbink

An Artificial Intelligence Approach to Concatenative Sound Synthesis
Noris Modh Norowi

Sound Synthesis with Deep Neural Networks
Jesse Engel

On Computer-Aided Orchestration
Marcelo Caetano

Gesture Data in Musical Composition
Marlon Schumacher and Marcelo Wanderley

Surveying Systems for Expressive Musical Performance by Computer
Alexis Kirke

Computer-Assisted Analysis of Musical Interpretation
Gerhard Widmer

Gesture Recognition in Interactive Music Performance
Dan Overholt

Designing Constraints for Composition and Performance with Computers
Thor Magnusson

Part IV: Emerging Developments in Musical AI

Machine Learning for Brain-Computer Music Interfacing
Eduardo R. Miranda and Satvik Venkatesh

Biological Neural Networks Synthesiser
Guy Ben-Ary

Sound and Music Biocomputing
Eduardo R. Miranda and Edward Braund

Musical Machine Learning with Biomemristors
Eduardo R. Miranda and Edward Braund

The Dawn of Quantum Computer Music
Eduardo R. Miranda

O autorze

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.

Blurb

This unique reference presents comprehensive coverage of the latest advances in research into enabling machines to listen to and compose new music. It includes chapters introducing what is known about human musical intelligence and on how this knowledge can be simulated with artificial intelligence (AI). The development of interactive musical robots and emerging new approaches to AI-based musical creativity are also introduced, including brain–computer music interfaces, bio-processors and quantum computing.

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.

Topics and features:

* 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

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.