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Computer Music

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The art of sound organization, also known as electroacoustic music, uses sounds not available to traditional music making, including pre-recorded, synthesized, and processed sounds. The body of work of such sound-based music (which includes electroacoustic art music, turntable composition, computer games, and acoustic and digital sound installations) has developed more rapidly than its musicology.

Digital media handles music as encoded physical energy, but humans consider music in terms of beliefs, intentions, interpretations, experiences, evaluations, and significations. In this book, drawing on work in computer science, psychology, brain science, and musicology, Marc Leman proposes an embodied cognition approach to music research that will help bridge this gap.

Computing in Musicology 14

Early Western music and the art music of the non-Western world both lack highly specified, standardized systems of notation. A serious impediment to the systematic study of early and non-Western music arises when a repertory has no extensive notational system, or multiple, non-standardized ones. In different ways, these conditions pertain to medieval and Renaissance music in the West, and to the art music of Asia, which has traditionally depended on oral tradition rather than notation.

In this original and provocative study of computational creativity in music, David Cope asks whether computer programs can effectively model creativity—and whether computer programs themselves can create. Defining musical creativity, and distinguishing it from creativity in other arts, Cope presents a series of experimental models that illustrate salient features of musical creativity. He makes the case that musical creativity results from a process that he calls inductive association, and he contends that such a computational process can in fact produce music creatively.

Methods, Models, and User Studies

The field of music query has grown from tentative beginnings in bibliographical systems of earlier decades to a substantial area of interdisciplinary studies in little more than a decade. This volume assembles recent studies from Europe and North America concerned with the query and analysis of musical data. Among these, methods for the synchronization of sound and symbolic data, for automatic analysis through perceptual rules, and for computing a "transportation" distance for thematic comparison are described.

Below the level of the musical note lies the realm of microsound, of sound particles lasting less than one-tenth of a second. Recent technological advances allow us to probe and manipulate these pinpoints of sound, dissolving the traditional building blocks of musicnotes and their intervalsinto a more fluid and supple medium. The sensations of point, pulse (series of points), line (tone), and surface (texture) emerge as particle density increases.

In this book, David Temperley addresses a fundamental question about music cognition: how do we extract basic kinds of musical information, such as meter, phrase structure, counterpoint, pitch spelling, harmony, and key from music as we hear it? Taking a computational approach, Temperley develops models for generating these aspects of musical structure. The models he proposes are based on preference rules, which are criteria for evaluating a possible structural analysis of a piece of music.

Computer Synthesis of Musical Style

Virtual Music is about artificial creativity. Focusing on the author's Experiments in Musical Intelligence computer music composing program, the author and a distinguished group of experts discuss many of the issues surrounding the program, including artificial intelligence, music cognition, and aesthetics.

Musicians begin formal training by acquiring a body of musical concepts commonly known as musicianship. These concepts underlie the musical skills of listening, performance, and composition. Like humans, computer music programs can benefit from a systematic foundation of musical knowledge. This book explores the technology of implementing musical processes such as segmentation, pattern processing, and interactive improvisation in computer programs.

As one of our highest expressions of thought and creativity, music has always been a difficult realm to capture, model, and understand. The connectionist paradigm, now beginning to provide insights into many realms of human behavior, offers a new and unified viewpoint from which to investigate the subtleties of musical experience. Music and Connectionism provides a fresh approach to both fields, using the techniques of connectionism and parallel distributed processing to look at a wide range of topics in music research, from pitch perception to chord fingering to composition.

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