Using discovered, polyphonic patterns to filter computer-generated music

Collins, Tom; Laney, Robin; Willis, Alistair and Garthwaite, Paul (2010). Using discovered, polyphonic patterns to filter computer-generated music. In: Proceedings of the International Conference on Computational Creativity, 7-9 Jan 2010, Lisbon Portugal.



A metric for evaluating the creativity of a music-generating system is presented, the objective being to generate mazurka-style music that inherits salient patterns from an original excerpt by Frédéric Chopin. The metric acts as a filter within our overall system, causing rejection of generated passages that do not inherit salient patterns, until a generated passage survives. Over fifty iterations, the mean number of generations required until survival was 12.7, with standard deviation 13.2. In the interests of clarity and replicability, the system is described with reference to specific excerpts of music. Four concepts–Markov modelling for generation, pattern discovery, pattern quantification, and statistical testing–are presented quite distinctly, so that the reader might adopt (or ignore) each concept as they wish.

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