Abstract
The key-profile model (originally proposed by Krumhansl and Schmuckler, and modified by Temperley) has proven to be a highly successful approach to key-finding. It appears that the key-profile model can be reinterpreted, with a few small modifications, as a Bayesian probabilistic model. This move sheds interesting light on a number of issues, including the psychological motivation for the key-profile model, other aspects of musical cognition such as metrical analysis, and issues such as ambiguity and expectation.
Cite
CITATION STYLE
Temperley, D. (2002). A Bayesian approach to key-finding. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2445, pp. 195–206). Springer Verlag. https://doi.org/10.1007/3-540-45722-4_18
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