Welcome!

My research program is driven by a central question of cognitive science: what kind of system can explain the process by which children acquire the infinitely expressive and complex system of language from limited exposure to noisy and ambiguous linguistic input? An overarching theme of my research is the development of formal systems that are informed by the insights and results of phonological theory and are also capable of successful and realistic modeling of phonological acquisition. My approach relies on computational modeling, grounded in probability and statistical learning theory, to develop models of phonological learning, to generate and test predictions of learning theories, and to analyze the relationship between the primary linguistic data and acquired phonological knowledge. Much of my work over the last twenty years has focused on the learning of hidden phonological structure, the relationship between the lexicon and the grammar, the availability of statistical cues in the learning input, and the nature of cognitive and learning biases. Since arriving at UMass in 2015, I have been increasingly incorporating experimental work into my research program. My recent work has integrated computational models of learning, theoretical phonology, and behavioral experimentation to examine the nature of the lexical and grammatical representations that underlie (morpho)phonological knowledge.

Follow the links above to access concise summaries with links to abstracts and PDFs or use tags on the right to view papers and talks by topic.

In 2018, I co-founded, with Joe Pater, the Society for Computation in Linguistics, and co-organized the first three annual meetings. Proceedings and more information can be found at ACL anthology and ScholarWorks.

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