This dissertation explores the relationship between English phonotactics – sequential dependencies between adjacent segments – and the metrical parse, which relies on the division of words into syllables. Most current theories of syllabification operate under the assumption that the phonotactic restrictions which co-determine syllable boundaries are constrained by word edges. For example, a syllable can never begin with a consonant sequence that is not also attested as a word onset. This view of phonotactics as categorical is outdated: for several decades now, psycholinguistic research employing monosyllables has shown that phonotactic knowledge is gradient, and that this gradience is projected from the lexicon and possibly also based on differences in sonority among consonants located at word margins. This dissertation is an attempt to reconcile syllabification theory with this modern view of phonotactics.
In what follows, I propose and defend a gradient metrical parsing model which assigns English syllable boundaries as a probabilistic function of the well-formedness relations that obtain between potential syllable onsets and offsets. I argue that this well-formedness is subserved by the same sources already established in the phonotactic literature: probabilistic generalizations over the word edges as well as sonority. In support of my proposal, I provide experimental evidence from five sources: (1) a pseudoword hyphenation experiment, (2) a reanalysis of a well-known, large-scale hyphenation study using real English words, (3) a forced-choice preference task employing nonwords presented as minimal stress pairs, (4) an online stress assignment experiment, and (5) a study of the speech errors committed by the participants of (4). The results of all studies converge in support of the gradient parsing model and correlate significantly with each other. Subsequent computer simulations suggest that the gradient model is preferred to the categorical alternative throughout all stages of lexical acquisition.
This dissertation contains co-authored material accepted for publication.
| Identifer | oai:union.ndltd.org:uoregon.edu/oai:scholarsbank.uoregon.edu:1794/24189 |
| Date | 11 January 2019 |
| Creators | Olejarczuk, Paul |
| Contributors | Kapatsinski, Vsevolod |
| Publisher | University of Oregon |
| Source Sets | University of Oregon |
| Language | en_US |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Rights | Creative Commons BY-ND 4.0-US |
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