Please use this identifier to cite or link to this item: http://hdl.handle.net/1880/46609
Title: MODELLING MUSIC: SYSTEMS, STRUCTURE, AND PREDICTION
Authors: Conklin, Darrell
Witten, Ian H.
Keywords: Computer Science
Issue Date: 1-May-1989
Abstract: This note opens with a commentary on the Georgescus' visionary paper entitled "A systems approach to music," which established an ambitious framework that encompasses a wide range of musical phenomena. Attention is concentrated on the higher-level aspects; in particular, the notion that the evolution of musical genres may exhibit structural instability by shifting to new musical paradigms, and the radical extension of this notion to the identification of morphogenesis in individual works. It is argued that structural discontinuities relate to creative processes rather than to artistic works per se, because they correspond to a breakdown of the listener's predictive model of the music. This focuses attention on the problem of deriving predictive models for particular musical pieces and genres--the subject of our own research. We equate predictive power with the ability of a model to compress the musical surface (roughly, text) of unseen works. Following a brief examination of theories for analyzing and generating music, the methodology of adaptive modeling and compression is set out, and extended from its conventional domain of strictly sequential natural language text to the much richer musical surface through the use of multiple viewpoints--specialized knowledge sources that deal with particular aspects of music. Finally, we discuss how the performance of models formed adaptively might be compared with that of live musicians, and outline an experiment currently in progress to establish how well human subjects can predict the musical surface of Bach Chorales.
URI: http://hdl.handle.net/1880/46609
Appears in Collections:Witten, Ian

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