Rule-based analysis and generation of music

Author: Spangler, Randall Richard

Year: 1999

Degree: Dissertation (Ph.D.)

Advisor: Goodman, Rodney M.

Committee Member: Unknown, Unknown

Option: Computation and Neural Systems

DOI: 10.7907/YXTQ-4057

Abstract

We develop a rule-based system for the purpose of analyzing musical examples to extract probabilistic rules of harmony; these rules are then used to generate new harmony in response to a melody input in real-time. A representation of music derived from the figured bass is developed which is suitable for embodying the harmonic content of a piece of music in a format suitable for machine learning. Algorithms are developed to convert music between this representation and standard MIDI files. An efficient algorithm for extracting raw rules from examples is presented, along with a comparison of its behavior to alternative methods such as hashing and hybrid algorithms. Processes to refine the rules produced by the previous algorithm into a more compact representation are shown, including considerations for weighting rules based on the types of errors they make in addition to their accuracy. Psychophysics experiments are performed to measure the perception of harmonic errors. The results of these experiments allow the development of new algorithms to generate rules which make less noticeable errors. The techniques developed above are used to build a rule-based system for real-time accompaniment.

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