MODELLING MUSIC: SYSTEMS, STRUCTURE, AND PREDICTION
Date
1989-05-01
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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.
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Computer Science