Assistant Professor Huteng Dai recently published an article titled, “An exception-filtering approach to phonotactic learning” in the April issue of Phonology.
DOI: https://doi.org/10.1017/S0952675725000028
Abstract: Phonotactic learning has been a fertile ground for research in the field of phonology. However, the challenge of lexical exceptions in phonotactic learning remains largely unexplored. Traditional learning models, which typically assume all observed input data to be grammatical, often blur the distinction between lexical exceptions and grammatical words, consequently skewing the learning results. To address this issue, this article innovates a categorical-grammar-plus-exception-filtering approach that harnesses the discrete nature of categorical grammars to filter out lexical exceptions using statistical criteria adapted from probabilistic models. Applied to naturalistic corpora from English, Polish and Turkish, the learnt grammars showed a high correlation with the acceptability judgements in behavioural experiments. Compared to benchmark models, the model performs increasingly better with data that contain a higher proportion of lexical exceptions, reaching its peak in learning Turkish non-local vowel phonotactics, highlighting its ability to handle lexical exceptions.
