Please use this identifier to cite or link to this item: http://hdl.handle.net/1880/46194
Title: PREDICTION AND ENTROPY OF MUSIC
Authors: Witten, Ian H.
Conklin, Darrell
Keywords: Computer Science
Issue Date: 1-Dec-1991
Abstract: The topic of music theory evaluation has recently aroused heated debate within the music theory community (Journal of Music Theory, 33(1), 1989). This paper develops a class of theories called \fImultiple viewpoint systems\fR. A multiple viewpoint theory of music is a collection of independent views on the musical surface, each modelling and predicting specific types of musical phenomena. When and why is one theory of music to be preferred over another? Some researchers believe that the notion of preference can be formalized, and others that it is subjective and based on esthetic criteria. This paper attempts a conciliation of these two views. On one hand, we believe that the best theory of a musical concept generates creative, esthetically more pleasing instances of the concept, and that this part of music theory evaluation cannot be truly objective. However, we conjecture that predictive power is a sufficient condition for esthetic quality. Predictive power is measured by performing inductive inference over a sample, and estimating the entropy, or complexity of the concept by applying rigorous tests to the theory. Musical concepts are not static; although some broad generalizations can apply, other generalizations are forced to change from piece to piece. To model this effect, we use a \fIlong-term\fR model which represents the general musical concept, and a \fIshort-term\fR model which adapts to a particular piece. The methods outlined in this paper are applied to the musical concept of "next event in a Bach chorale melody". Short and long-term multiple viewpoint systems are induced from a sample, and applications of the preference evaluation are given.
URI: http://hdl.handle.net/1880/46194
Appears in Collections:Witten, Ian

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