Learning Nonlocal Phonotactics in a Strictly Piecewise Probabilistic Phonotactic Model
Keywords:Nonlocal phonotactics, Quechua, Phonotactic model, Strictly Piecewise languages
AbstractPhonotactic 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).
Published by the LSA with permission of the author(s) under a CC BY 3.0 license.