This anthology provides an informative and timely introduction to ongoing research on music as a cognitive process, bringing a new coherence to the emerging science of musical activity. Following the foreword, which is based on a conversation with Marvin Minsky, 26 contributions explore musical composition, analysis, performance, perception, and learning and tutoring. Their goal is to discover how these activities can be interpreted, understood, modeled, and supported through the use of computer programs. Each chapter is put into perspective by the editors, and empirical investigations are framed by a discussion of the nature of cognitive musicology and of epistemological problems of modeling musical action. The contributions, drawn from two international workshops on AI and Music held in 1988 and 1989, are grouped in seven sections. Topics in these sections take up two views of the nature of cognitive musicology (Kugel, Laske), principles of modeling musical activity (Balaban, Bel, Blevis, Glasgow and Jenkins, Courtot, Smoliar), approaches to music composition (Ames and Domino, Laske, Marsella, Riecken), music analysis by synthesis (Cope, Ebcioglu, Maxwell), realtime performance of music (Bel and Kippen, Ohteru and Hashimoto), music perception (Desain and Honing, Jones, Miller and Scarborough, Linster), and learning/tutoring (Baker, Widmer).

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.

Mathematical Music offers a concise and easily accessible history of how mathematics was used to create music. The story presented in this short, engaging volume ranges from ratios in antiquity to random combinations in the 17th century, 20th-century statistics, and contemporary artificial intelligence. This book provides a fascinating panorama of the gradual mechanization of thought processes involved in the creation of music. How did Baroque authors envision a composition system based on combinatorics? What was it like to create musical algorithms at the beginning of the 20th century, before the computer became a reality? And how does this all explain today’s use of artificial intelligence and machine learning in music? In addition to discussing the history and the present state of mathematical music, Braguinski also takes a look at what possibilities the near future of music AI might hold for listeners, musicians, and the society. Grounded in research findings from musicology and the history of technology, and written for the non-specialist general audience, this book helps both student and professional readers to make sense of today’s music AI by situating it in a continuous historical context.

An authority on creativity introduces us to AI-powered computers that are creating art, literature, and music that may well surpass the creations of humans. Today's computers are composing music that sounds “more Bach than Bach,” turning photographs into paintings in the style of Van Gogh's Starry Night, and even writing screenplays. But are computers truly creative—or are they merely tools to be used by musicians, artists, and writers? In this book, Arthur I. Miller takes us on a tour of creativity in the age of machines. Miller, an authority on creativity, identifies the key factors essential to the creative process, from “the need for introspection” to “the ability to discover the key problem.” He talks to people on the cutting edge of artificial intelligence, encountering computers that mimic the brain and machines that have defeated champions in chess, Jeopardy!, and Go. In the central part of the book, Miller explores the riches of computer-created art, introducing us to artists and computer scientists who have, among much else, unleashed an artificial neural network to create a nightmarish, multi-eyed dog-cat; taught AI to imagine; developed a robot that paints; created algorithms for poetry; and produced the world's first computer-composed musical, Beyond the Fence, staged by Android Lloyd Webber and friends. But, Miller writes, in order to be truly creative, machines will need to step into the world. He probes the nature of consciousness and speaks to researchers trying to develop emotions and consciousness in computers. Miller argues that computers can already be as creative as humans—and someday will surpass us. But this is not a dystopian account; Miller celebrates the creative possibilities of artificial intelligence in art, music, and literature.

This book is a survey and analysis of how deep learning can be used to generate musical content. The authors offer a comprehensive presentation of the foundations of deep learning techniques for music generation. They also develop a conceptual framework used to classify and analyze various types of architecture, encoding models, generation strategies, and ways to control the generation. The five dimensions of this framework are: objective (the kind of musical content to be generated, e.g., melody, accompaniment); representation (the musical elements to be considered and how to encode them, e.g., chord, silence, piano roll, one-hot encoding); architecture (the structure organizing neurons, their connexions, and the flow of their activations, e.g., feedforward, recurrent, variational autoencoder); challenge (the desired properties and issues, e.g., variability, incrementality, adaptability); and strategy (the way to model and control the process of generation, e.g., single-step feedforward, iterative feedforward, decoder feedforward, sampling). To illustrate the possible design decisions and to allow comparison and correlation analysis they analyze and classify more than 40 systems, and they discuss important open challenges such as interactivity, originality, and structure. The authors have extensive knowledge and experience in all related research, technical, performance, and business aspects. The book is suitable for students, practitioners, and researchers in the artificial intelligence, machine learning, and music creation domains. The reader does not require any prior knowledge about artificial neural networks, deep learning, or computer music. The text is fully supported with a comprehensive table of acronyms, bibliography, glossary, and index, and supplementary material is available from the authors' website.

A multidisciplinary introduction to the field of computational creativity, analyzing the impact of advanced generative technologies on art and music. As algorithms get smarter, what role will computers play in the creation of music, art, and other cultural artifacts? Will they be able to create such things from the ground up, and will such creations be meaningful? In Beyond the Creative Species, Oliver Bown offers a multidisciplinary examination of computational creativity, analyzing the impact of advanced generative technologies on art and music. Drawing on a wide range of disciplines, including artificial intelligence and machine learning, design, social theory, the psychology of creativity, and creative practice research, Bown argues that to understand computational creativity, we must not only consider what computationally creative algorithms actually do, but also examine creative artistic activity itself.

"This book offers an international platform to bring together academics, researchers, lecturers, decision makers, policy makers, and practitioners to share new theories, research findings, and case studies, to enhance understanding and collaboration in business, digital strategies, disruptive innovation, green growth, and technology in Asia"--

This must-have book is a comprehensive yet accessible guide to copyright and related rights in the music industry, illustrated with relevant cases and real world examples. Key features include: • An engaging and approachable writing style • A practical orientation for those in the industry and their advisors • The impact of social media on copyright infringement, management and remedies • Accessible explanations of key concepts in copyright and related rights, as well as commonly misunderstood topics such as sampling and fair use.