Learning Nonlocal Phonotactics in a Strictly Piecewise Probabilistic Phonotactic Model

Phonotactic learning is a crucial aspect of phonological acquisition and has figured significantly in computational research in phonology (Prince & Tesar 2004). However, one persistent challenge for this line of research is inducing non-local co-occurrence patterns (Hayes & Wilson 2008). The current study develops a probabilistic phonotactic model based on the Strictly Piecewise class of subregular languages (Heinz 2010). The model successfully learns both segmental and featural representations, and correctly predicts the acceptabilities of the nonce forms in Quechua (Gouskova & Gallagher 2020)

Time and Phonology: Precedence-Based Representations

A major factor hindering the establishment of a successful neuroscience of phonology centers around the biological viability of a given phonological framework. The ultimate aim of this project is to find potential alignments between linguistics and neuroscience. In this vein, the main topic of the thesis rests upon establishing the minimal complexity requirements for a phonological representation that is biologically plausible, cognitively sound, and empirically motivated. Heeding Minimalist proposals (Chomsky, 1995) that encourage efficiency in computation and economy in representation, I embark on an in-depth exploration of the parameters of cognition that are necessary and sufficient in a phonological representation while discounting the processes and parameters that can be said to be “domain-general”. To that end, I take seriously Ernst Po ̈ppel’s (2004) exhortation to consider the role of temporal events like linear order and precedence in the study of cognitive systems like phonology by surveying the literature on time perception. The conclusions support a separation of order from phonological representations, extending the scope of substance-freeness (Hale and Reiss, 2000) by characterizing order as substance. Such an approach can contribute to thoroughly defining the object of study and offer insight that narrows the search space for potential bridges