Doctor of Philosophy, The Ohio State University, 2003, Music

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. 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.

Committee: David Huron (Advisor) Subjects: Music; Psychology, Cognitive