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http://hdl.handle.net/11375/32577Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Schutz, Michael | - |
| dc.contributor.author | Zhou, Jackie Zhi Qi | - |
| dc.date.accessioned | 2025-10-23T15:54:13Z | - |
| dc.date.available | 2025-10-23T15:54:13Z | - |
| dc.date.issued | 2026 | - |
| dc.identifier.uri | http://hdl.handle.net/11375/32577 | - |
| dc.description.abstract | Mode and emotion are central to the expressive power of music, yet both present challenges for empirical study. This thesis advances understanding in two complementary ways. The first study reconsiders mode, a foundational property of tonal music traditionally treated as a binary distinction between “major” and “minor.” Using a corpus of 72 piano preludes by Bach, Chopin, and Shostakovich, we conceptualise relative mode as a spectrum and evaluate it across three approaches: perceptual, analytical, and computational. Results show moderate-to-strong alignment between the approaches, with even untrained listeners demonstrating sensitivity to granular modality. Further findings indicate that expert analyses are the most discriminating, however, computational estimates provide a scalable alternative with alignment to other approaches. Together, these results establish relative mode as a perceptually valid and computationally accessible construct for music cognition, theory, and information retrieval. The second study examines whether traditional linear models suffice for explaining emotional responses across both the common-practice period (CPP; ~1650–1900) and later repertoire. We compare linear and nonlinear regression techniques in predicting valence ratings of preludes by Bach and Chopin (CPP) as well as Shostakovich and Debussy (non-CPP), using four well-established musical properties: relative mode, attack rate, pitch height, and amplitude. Results showed that linear and nonlinear models performed similarly for CPP composers. In contrast, nonlinear approaches substantially outperformed linear ones for Shostakovich and especially for Debussy, whose harmonically ambiguous and stylistically innovative preludes served as a case study for the benefits of nonlinear modeling. These findings demonstrate that although linear models are sufficient for CPP repertoire, capturing emotional responses to non-CPP music—particularly Debussy—requires more flexible, nonlinear approaches. | en_US |
| dc.language.iso | en | en_US |
| dc.title | Beyond the binary and linearity: A continuum model of modality and nonlinear approaches to musical emotion | en_US |
| dc.type | Thesis | en_US |
| dc.contributor.department | Psychology | en_US |
| dc.description.degreetype | Thesis | en_US |
| dc.description.degree | Master of Science (MSc) | en_US |
| dc.description.layabstract | Music has a powerful ability to convey emotions but understanding how is far less obvious. Traditional research has relied on simple rules—for example, major keys sound brighter than minor ones, and faster music feels more energetic. This thesis challenges these assumptions in two ways. First, we show that “mode,” usually labelled as major or minor, can instead be understood on a spectrum. This approach better matches how listeners actually hear music and aligns with expert analysis and computer models. Second, we test whether common statistical methods can explain emotional responses to more modern music, using Claude Debussy’s preludes as a case study. We find that although simple models work well for earlier classical composers such as Bach and Chopin, more flexible nonlinear methods are needed for latter composers such as Shostakovich and Debussy. Together, these studies move beyond traditional assumptions of binary modality and linear modeling, offering new tools for understanding how music across history communicates emotion. | en_US |
| Appears in Collections: | Open Access Dissertations and Theses | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Zhou_JackieZhiQi_2025-September_MSc.pdf | 1.79 MB | Adobe PDF | View/Open |
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