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Dynamic Melodic Expectancy

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Dynamic Melodic Expectancy DYNAMIC MELODIC EXPECTANCY DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Bret J. Aarden, M.A. The Ohio State University 2003 Dissertation Committee: Approved by Professor David Huron, Adviser Professor Patricia Flowers Adviser Professor Mari Riess Jones School of Music Professor Lee Potter ABSTRACT The most common method for measuring melodic expectancy is the “probe-tone” design, which relies on a retrospective report of expectancy. Here a direct measure of expectancy is introduced, one that uses a speeded, serial categorization task. An analysis of the reaction time data showed that “Implication-Realization” contour models of melodic expectancy provide a good fit. Further analysis suggests that some assumptions of these contour models may not be valid. The traditional “key profile” model of tonality was not found to contribute significantly to the model. Following Krumhansl’s (1990) argument that tonality is learned from the statistical distribution of scale degrees, a tonality model based on the actual probability of scale degrees did significantly improve the fit of the model. It is proposed that the probe-tone method for measuring key profiles encourages listeners to treat the probe tone as being in phrase-final position. Indeed, the key profile was found to be much more similar to the distribution of phrase-final notes than to the distribution of all melodic notes. A second experiment measured reaction times to notes that subjects expected to be phrase-final. In this experiment the key profile contributed significantly to the fit of the model. ii It is concluded that the probe-tone design creates a task demand to hear the tone as a phrase-final note, and the key profile reflects a learned sensitivity to the distribution of notes at ends of melodies. The “key profile” produced by the new reaction-time design is apparently related to the general distribution of notes in melodies. The results of this study indicate that the relationship between melodic structure and melodic expectation is more straightforward than has been previously demonstrated. Melodic expectation appears to be related directly to the structure and distribution of events in the music. iii ACKNOWLEDGMENTS There are a number of people whose contributions to this dissertation need to be acknowledged. I would like to thank my advisor David Huron for his endless support and pragmatic advice over the course of this project. I believe his lab has been an unparalleled place to pursue the musicological study of psychology. Without Paul von Hippel’s work at Ohio State the concept for these experiments would never have occurred to me. Many office and coffeehouse conversations with David Butler informed my thinking about the state of music psychology and are reflected in the grundgestalt of this work. Finally, I would especially like to thank my wife Althea for numerous conversations and pep talks, such as the one that led to chapter 5. I hope you can see your good influences reflected here. iv VITA 2002................................................................Graduate Minor, Quantitative Psychology The Ohio State University 2001................................................................M. A., Music Theory The Ohio State University 1998 – present................................................Dean’s Distinguished Fellow, Ohio State University 1998................................................................B. A., New College of Florida PUBLICATIONS Research publications 1. Aarden, Bret. (2002). Expectancy vs. retrospective perception: Reconsidering the effects of schema and continuation judgments on measures of melodic expectancy. In Proceedings of the 7th International Conference on Music Perception and Cognition. Ed. C. Stevens, D. Burnham, G. McPherson, E. Schubert, and J. Renwick. Adelaide: Causal Productions. 2. Aarden, Bret and Huron, David. (2001). Mapping European folksong: Geographical localization of musical features. Computing in Musicology, 12:169– 183. FIELDS OF STUDY Major Field: Music v TABLE OF CONTENTS Abstract............................................................................................................................... ii Acknowledgments.............................................................................................................. iv Vita...................................................................................................................................... v List of Tables ...................................................................................................................viii List of Figures.................................................................................................................... ix Chapter 1: Introduction....................................................................................................... 1 Chapter 2: Theories of Melodic Expectancy ...................................................................... 6 The Grand Illusion: Harmonic Influences on Melody.................................................... 7 An Overview and Critique of the Tonal Hierarchy Theory.......................................... 11 The Static Key Profile............................................................................................... 13 Ordering Through Time............................................................................................ 15 Effects of Stimulus Structure.................................................................................... 17 Equating Chord With Key ........................................................................................ 22 Problems Explaining the Key Profiles...................................................................... 25 An Overview and Critique of the Implication-Realization Model ............................... 27 The Gestalt principles ............................................................................................... 30 Redundancy............................................................................................................... 32 Regression to the Mean............................................................................................. 35 Chapter 3: Methods of Measurement................................................................................ 37 Previous Methods for Measuring Melodic Expectancy................................................ 38 A New Method.............................................................................................................. 39 vi Chapter 4: Expectancy for Continuation (Experiment 1) ................................................. 42 Methods......................................................................................................................... 43 Stimuli....................................................................................................................... 43 Equipment................................................................................................................. 45 Subjects and Procedure............................................................................................. 45 Results........................................................................................................................... 48 Univariate Main Effects............................................................................................ 48 Multivariate Analysis................................................................................................ 53 Discussion..................................................................................................................... 57 Overview................................................................................................................... 66 Chapter 5: Expectancy for Closure (Experiment 2).......................................................... 69 Methods......................................................................................................................... 69 Stimuli....................................................................................................................... 70 Subjects, Equipment, and Procedure ........................................................................ 71 Results........................................................................................................................... 72 Univariate Main Effects............................................................................................ 72 Multivariate analysis................................................................................................. 75 Discussion..................................................................................................................... 79 Further evidence from key-finding ........................................................................... 80 Conclusions............................................................................................................... 84 Chapter 6: Re-examining the Implication-Realization Model.......................................... 86 The 5-Factor Parameters model.................................................................................... 86 The Archetype Model ................................................................................................... 88 The Statistical Model ...................................................................................................
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