computational phonology

Regular and Polyregular Theories of Reduplication

We show a mismatch between the generative capacity of reduplication and the theories which model it.

Benchmarking Compositionality with Formal Languages

A novel method for sampling a class of subsequential string transductions encoding homomorphisms allows rigorous testing of learning models' capacity for compositionality.

History of Phonology: Learnability

This chapter examines the brief but vibrant history of learnability in phonology.

Phonological Abstractness in the Mental Lexicon

We overview the notion of phonological abstractness, various types of evidence for it, and consequences for linguistics and psychology.

Structure and Learning in Natural Language

My doctoral dissertation, examining the relationship between abductive inference and algebraically structured hypothesis spaces, giving a general form for grammar learning over arbitrary linguistic structure.

Typology Emerges from Simplicity in Representations and Learning

We derive the well-studied subregular classes of formal languages, which computationally characterize natural language typology, purely from the perspective of algorithmic learning problems.

Computational Restrictions on Iterative Prosodic Processes

We formalize various iterative prosodic processes including stress, syllabification and epenthesis using logical graph transductions, showing that the necessary use of fixed point operators without quantification restricts them to a structured subclass of subsequential functions.

Computational Locality in Nonlinear Morphophonology

We present an automata-theoretic analysis of locality in nonlinear phonology and morphology.

Strong Generative Capacity of Morphological Processes

We analyze divergences in strong generative capacity between morphological processes that are equivalent in weak generative capacity.

The Computational Power of Harmony

We overview vowel harmony computationally, describing necessary and sufficient conditions on phonotactics, processes, and learning.