<p>In most aspects of music--e.g., tempo, intensity, and rhythm--the emotional coloring of a melody is due at least in part to physical imitation of the characteristics of emotional expression in human behavior. Thus excited, happy melodies are fast and loud, with syncopated rhythms, whereas subdued sad melodies are slow and quiet, with more even rhythms. The tonality of a melody (e.g. major or minor) also conveys emotion, but unlike other aspects of music, the basis for its affective impact is not clear. This thesis examines the hypothesis that different collections of musical tones are associated with specific emotions because they mimic the natural relationship between emotion and tonality present in the human voice. To evaluate this possibility, I have conducted acoustical analyses on databases of music and speech drawn from a variety of cultures, and compared the tonal characteristics of emotional expression between these two forms of social communication. I find that: (1) the melodic characteristics of music and the prosodic characteristics of speech co-vary when examined across cultures; (2) the principal tonal characteristics of melodies composed in tonalities associated with positive/excited emotion and negative/subdued emotion are much the same in different cultures; (3) cross-cultural tonal similarities in music parallel cross-cultural tonal similarities in vocal expression; and (4) the tonal characteristics of emotional expression in the voice convey distinct emotions, thereby accounting for the specificity of emotional association in musical tonality. These findings, and the implausibility of alternative explanations that could account for them, suggest that the affective impact of musical tonality derives from mimicry of the tonal characteristics of vocalization in different emotional states.</p> / Dissertation
| Identifer | oai:union.ndltd.org:DUKE/oai:dukespace.lib.duke.edu:10161/5522 |
| Date | January 2012 |
| Creators | Bowling, Daniel Liu |
| Contributors | Purves, Dale |
| Source Sets | Duke University |
| Detected Language | English |
| Type | Dissertation |
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