Phonetics and Phonology Commons^™

Learning Phonology With Sequence-To-Sequence Neural Networks, Brandon Prickett

Doctoral Dissertations

This dissertation tests sequence-to-sequence neural networks to see whether they can simulate human phonological learning and generalization in a number of artificial language experiments. These experiments and simulations are organized into three chapters: one on opaque interactions, one on computational complexity in phonology, and one on reduplication. The first chapter focuses on two biases involving interactions that have been proposed in the past: a bias for transparent patterns and a bias for patterns that maximally utilize all of the processes in a language. The second chapter looks at harmony patterns of varying complexity to see whether both Formal Language Theory …