tailieunhanh - Báo cáo khoa học: "The Influence of Discourse on Syntax A Psycholinguistic Model of Sentence Processing"

Probabilistic models of sentence comprehension are increasingly relevant to questions concerning human language processing. However, such models are often limited to syntactic factors. This paper introduces a novel sentence processing model that consists of a parser augmented with a probabilistic logic-based model of coreference resolution, which allows us to simulate how context interacts with syntax in a reading task. Our simulations show that a Weakly Interactive cognitive architecture can explain data which had been provided as evidence for the Strongly Interactive hypothesis. . | The Influence of Discourse on Syntax A Psycholinguistic Model of Sentence Processing Amit Dubey Abstract Probabilistic models of sentence comprehension are increasingly relevant to questions concerning human language processing. However such models are often limited to syntactic factors. This paper introduces a novel sentence processing model that consists of a parser augmented with a probabilistic logic-based model of coreference resolution which allows us to simulate how context interacts with syntax in a reading task. Our simulations show that a Weakly Interactive cognitive architecture can explain data which had been provided as evidence for the Strongly Interactive hypothesis. 1 Introduction Probabilistic grammars have been found to be useful for investigating the architecture of the human sentence processing mechanism Jurafsky 1996 Crocker and Brants 2000 Hale 2003 Boston et al. 2008 Levy 2008 Demberg and Keller 2009 . For example probabilistic models shed light on so-called locality effects contrast the non-probabilistic hypothesis that dependants which are far away from their head always cause processing difficulty for readers due to the cost of storing the intervening material in memory Gibson 1998 compared to the probabilistic prediction that there are cases when faraway dependants facilitate processing because readers have more time to predict the head Levy 2008 . Using a computational model to address fundamental questions about sentence comprehension motivates the work in this paper. So far probabilistic models of sentence processing have been largely limited to syntactic factors. This is unfortunate because many outstanding questions in psycholinguistics concern interactions between different levels of processing. This paper addresses this gap by building a computational model which simulates the influence of discourse on syntax. Going beyond the confines of syntax alone is a sufficiently important problem that it has attracted attention from other .