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.
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Temperley, D. (2002). A Bayesian Approach to Key-Finding. In: Anagnostopoulou, C., Ferrand, M., Smaill, A. (eds) Music and Artificial Intelligence. ICMAI 2002. Lecture Notes in Computer Science(), vol 2445. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45722-4_18
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DOI: https://doi.org/10.1007/3-540-45722-4_18
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