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ERIC Number: EJ789298
Record Type: Journal
Publication Date: 2008-Mar
Pages: 27
Abstractor: Author
Reference Count: 67
ISSN: ISSN-0364-0213
A Probabilistic Model of Melody Perception
Temperley, David
Cognitive Science, v32 n2 p418-444 Mar 2008
This study presents a probabilistic model of melody perception, which infers the key of a melody and also judges the probability of the melody itself. The model uses Bayesian reasoning: For any "surface" pattern and underlying "structure," we can infer the structure maximizing P(structure [vertical bar] surface) based on knowledge of P(surface, structure). The probability of the surface can then be calculated as the sum of P(surface, structure), summed over all structures. In this case, the surface is a pattern of notes; the structure is a key. A generative model is proposed, based on three principles: (a) melodies tend to remain within a narrow pitch range; (b) note-to-note intervals within a melody tend to be small; and (c) notes tend to conform to a distribution (or key profile) that depends on the key. The model is tested in three ways. First, it is tested on its ability to identify the keys of a set of folksong melodies. Second, it is tested on a melodic expectation task in which it must judge the probability of different notes occurring given a prior context; these judgments are compared with perception data from a melodic expectation experiment. Finally, the model is tested on its ability to detect incorrect notes in melodies by assigning them lower probabilities than the original versions. (Contains 10 figures, 2 tables, and 18 notes.)
Lawrence Erlbaum. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A