State-of-the-art models for the perception of grouping structure in music do not attempt to account for disagreements among listeners. But understanding these disagreements, sometimes regarded as noise in psychological studies, may be essential to fully understanding how listeners perceive grouping structure. Over the course of four studies in different disciplines, this thesis develops and presents evidence to support the hypothesis that attention is a key factor in accounting for listeners' perceptions of boundaries and groupings, and hence a key to explaining their disagreements. First, we conduct a case study of the disagreements between two listeners. By studying the justi cations each listener gave for their analyses, we argue that the disagreements arose directly from differences in attention, and indirectly from differences in information, expectation, and ontological commitments made in the opening moments. Second, in a large-scale corpus study, we study the extent to which acoustic novelty can account for the boundary perceptions of listeners. The results indicate that novelty is correlated with boundary salience, but that novelty is a necessary but not su cient condition for being perceived as a boundary. Third, we develop an algorithm that optimally reconstructs a listener's analysis in terms of the patterns of similarity within a piece of music. We demonstrate how the output can identify good justifications for an analysis and account for disagreements between two analyses. Finally, having introduced and developed the hypothesis that disagreements between listeners may be attributable to differences in attention, we test the hypothesis in a sequence of experiments. We find that by manipulating the attention of participants, we are able to influence the groupings and boundaries they find most salient. From the sum of this research, we conclude that a listener's attention is a crucial factor affecting how listeners perceive the grouping structure of music.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:765762 |
Date | January 2014 |
Creators | Smith, Jordan |
Publisher | Queen Mary, University of London |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://qmro.qmul.ac.uk/xmlui/handle/123456789/27225 |
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