Expectation in Melody: The Influence of Context and Learning

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Wiggins, Geraint A. ; Pearce, Marcus T. (2006)
  • Publisher: University of California Press

The Implication-Realization (IR) theory (Narmour, 1990) posits two cognitive systems involved in the generation of melodic expectations: The first consists of a limited number of symbolic rules that are held to be innate and universal; the second reflects the top-down influences of acquired stylistic knowledge. Aspects of both systems have been implemented as quantitative models in research which has yielded empirical support for both components of the theory (Cuddy & Lunny, 1995; Krumhansl, 1995a, 1995b; Schellenberg, 1996, 1997). However, there is also evidence that the implemented bottom-up rules constitute too inflexible a model to account for the influence of the musical experience of the listener and the melodic context in which expectations are elicited. A theory is presented, according to which both bottom-up and top-down descriptions of observed patterns of melodic expectation may be accounted for in terms of the induction of statistical regularities in existing musical repertoires. A computational model that embodies this theory is developed and used to reanalyze existing experimental data on melodic expectancy. The results of three experiments with increasingly complex melodic stimuli demonstrate that this model is capable of accounting for listeners’ expectations as well as or better than the two-factor model of Schellenberg (1997).
  • References (102)
    102 references, page 1 of 11

    AARDEN, B. (2003). Dynamic melodic expectancy. Unpublished doctoral dissertation, Ohio State University, Columbus.

    AHA, D. W., & BANKERT, R. L. (1996). A comparative evaluation of sequential feature selection algorithms. In D. Fisher & H. J. Lenz (Eds.), Learning from data: AI and statistics V (pp. 199-206). New York: Springer.

    BALZANO, G. J. (1982). The pitch set as a level of description for studying musical pitch perception. In M. Clynes (Ed.), Music, mind and brain (pp. 321-351). New York: Plenum.

    BERGESON, T. R. (1999). Melodic expectancy in infancy. Journal of the Acoustical Society of America, 106, 2285.

    BHARUCHA, J. J. (1984). Anchoring effects in music: The resolution of dissonance. Cognitive Psychology, 16, 485-518.

    BHARUCHA, J. J. (1987). Music cognition and perceptual facilitation: A connectionist framework. Music Perception, 5, 1-30.

    BHARUCHA, J. J. (1993). Tonality and expectation. In R. Aiello (Ed.), Musical perceptions (pp. 213-239). Oxford: Oxford University Press.

    BHARUCHA, J. J., & STOECKIG, K. (1986). Reaction time and musical expectancy: Priming of chords. Journal of Experimental Psychology: Human Perception and Performance, 12, 403-410.

    BLUM, A., & LANGLEY, P. (1997). Selection of relevant features and examples in machine learning. Artificial Intelligence, 97, 245-271.

    CARLSEN, J. C. (1981). Some factors which influence melodic expectancy. Psychomusicology, 1, 12-29.

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