{"pk":24105,"title":"A hierarchical Bayesian model for syntactic priming","subtitle":null,"abstract":"The effect of syntactic priming exhibits three well-documented empirical properties: the lexical boost, the inverse frequency effect, and the asymmetrical decay. We aim to show how these three empirical phenomena can be reconciled in a general learning framework, the hierarchical Bayesian model (HBM). The model represents syntactic knowledge in a hierarchical structure of syntactic statistics, where a lower level represents the verb-specific biases of syntactic decisions, and a higher level represents the abstract bias as an aggregation of verb-specific biases. This knowledge is updated in response to experience by Bayesian inference. In simulations, we show that the HBM captures the above-mentioned properties of syntactic priming. The results indicate that some properties of priming which are usually explained by a residual activation account can also be explained by an implicit learning account. We also discuss the model's implications for the lexical basis of syntactic priming.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"Linguistics; Psychology; Language Production; Statistical learning; Syntax; Bayesian modeling; Computational Modeling"}],"section":"Papers with Poster Presentation","is_remote":true,"remote_url":"https://escholarship.org/uc/item/9cc8p5fk","frozenauthors":[{"first_name":"Weijie","middle_name":"","last_name":"Xu","name_suffix":"","institution":"University of California, Irvine","department":""},{"first_name":"Richard","middle_name":"","last_name":"Futrell","name_suffix":"","institution":"UC Irvine","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2024-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/24105/galley/13699/download/"},{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/24105/galley/20877/download/"}]}