Bayesian Models of Musical Structure and Cognition

This paper explores the application of Bayesian probabilistic modeling to issues of music cognition and music theory. The main concern is with the problem of key-finding: the process of inferring the key from a pattern of notes. The Bayesian perspective leads to a simple, elegant, and highly effective model of this process; the same approach can also be extended to other aspects of music perception, such as metrical structure and melodic structure. Bayesian modeling also relates in interesting ways to a number of other musical issues, including musical tension, ambiguity, expectation, and the quantitative description of styles and stylistic differences.