Understanding Music with AI
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).
M. Balaban is Senior Lecturer in the Department of Mathematics and Computer Science at Ben-Gurion University. K. Ebcioglu is Research Scientist in the Computer Sciences Department, IBM Thomas J. Watson Research Center. 0. Laske is a composer and President of NEWCOMP, Inc., The New England Computer Arts Association, Inc.