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Metrical and prosodic structure in optimality theory
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Hyde, Brett D.. Metrical and prosodic structure in optimality theory. Retrieved from https://doi.org/doi:10.7282/T3S46QRF

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TitleMetrical and prosodic structure in optimality theory
NameHyde, Brett D. (Author); Rutgers University; Graduate School-New Brunswick
Date Created2001
Other Date2001 (degree)
SubjectLinguistics, Phonology, stress, metrical structure, prosodic structure, Accents and accentuation, Metrical phonology, Prosodic analysis (Linguistics)
Extent215 p.
DescriptionThis dissertation examines four components of a theory of metrical stress-- the prosodic hierarchy, the system of prosodic prominence, the metrical grid, and the slope category system-- and investigates how Optimality Theoretic constraints restrict or facilitate interaction between them. The proposal is comprehensive in that it examines each of the basic types of stress alternation? binary, ternary, and unbounded?both in weight-sensitive and weight-insensitive systems. The proposal's focus, however, is the discrepancy between the wide range of binary patterns that standard accounts predict and the much smaller range of patterns that are actually attested. Of particular concern is the standard account?s over-generation of iambic patterns. In pursuit of greater restrictiveness, the proposed approach departs from the structural assumptions of current approaches in several ways. The proposed account insists on strict succession (or exhaustive parsing),tolerates improper bracketing, makes violable the foot-stress relationship, and allows prosodic categories to share entries on the metrical grid. The proposal also departs from the standard account in the division of labor between symmetrical constraints, such as Alignment, and asymmetrical constraints, such as Non Finality. Although Alignment still figures prominently in the proposed account, constraints like Non Finality play a more central role in establishing basic typologies. Given the structural assumptions, this shift in emphasis results in a different, and much smaller, range of predicted patterns.
NotePh.D.
Genrethesis, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/T3S46QRF
LanguageEnglish
CollectionRutgers Optimality Archive, Graduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work
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