Learning nonlocal phonotactics in Strictly Piecewise phonotactic model - Huteng Dai (Society for Computation in Linguistics, 2021)
Phonotactic 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; G & G henceforth).
Keywords: Formal Language Theory; statistical learning; corpus study; phonotactics