computational phonology

This article examines whether the computational properties of phonology hold across spoken and signed languages, using model theory and logical transductions.

We analyze the expressivity of a variety of recurrent encoder-decoder networks, showing they are limited to learning subsequential functions, and connecting RNNs with attention mechanisms to a class of deterministic 2-way transducers.

We provide an automata-theoretic characterization of templatic morphology, extending strict locality to consider n-ary functions.

We provide an automata-theoretic characterization of tonal phonology, extending strict locality to consider n-ary functions.

I provide a vector space characterization of the Star-Free and Locally Threshold testable classes of formal languages, over arbitrary data structures.

We describe a partial order on the space of model-theoretic constraints and a learning algorithm for constraint inference.

We describe the finite-state nature of root-and-pattern morphology using Semitic as a case study, and discuss issues of finiteness vs. infinity, and template emergence.

I show the complexity of several signed processes is subregular across speech and sign using string representations.