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2021
DOI: 10.31234/osf.io/w89zt
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Dynamical Cognitive Modeling of Syntactic Processing and Eye Movement Control in Reading

Abstract: Integrating eye-movement control and sentence processing would mark an important step forward for mathematical models of natural language processing. We present an integrated approach by combining the SWIFT model of eye-movement control (Engbert et al., 2005) with key components of the LV05 (Lewis & Vasishth, 2005) parser. The integrated generative model can reproduce reading time patterns that have been explained in terms of similarity-based interference in the psycholinguistic literature. A crucial p… Show more

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Cited by 4 publications
(4 citation statements)
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References 30 publications
(48 reference statements)
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“…We focus only on the critical region because, strictly speaking, the model's predictions are for this region only: the retrieval of the subject NP should be triggered when the verb is read. In order to fully interpret interference effects that occur before or after the verb, a more sophisticated understanding of the eye-parser relationship is needed, which is beyond the current capabilities of the Lewis & Vasishth model (see Rabe et al, 2023).…”
Section: Discussionmentioning
confidence: 99%
“…We focus only on the critical region because, strictly speaking, the model's predictions are for this region only: the retrieval of the subject NP should be triggered when the verb is read. In order to fully interpret interference effects that occur before or after the verb, a more sophisticated understanding of the eye-parser relationship is needed, which is beyond the current capabilities of the Lewis & Vasishth model (see Rabe et al, 2023).…”
Section: Discussionmentioning
confidence: 99%
“…We chose these three measures because these are the reading time measures reported in Van Dyke (2007). First-pass regressions were also reported in Van Dyke ( 2007), but mapping first-pass regression probability to latent higher-level cognitive processes requires a more sophisticated modeling environment incorporating low-level eye-movement control processes; such an environment is currently under development (Rabe, Paape, et al, 2021;Rabe, Chandra, et al, 2021).…”
Section: Predictionsmentioning
confidence: 99%
“…There are two parameters that we need to model to fit the reading model to the corpus data: F and f . We will estimate them using Bayesian techniques (see Dotlačil, 2018 , Brasoveanu and Dotlačil, 2018 , Brasoveanu and Dotlačil, 2019 , Brasoveanu and Dotlačil, 2020 ; Rabe et al, 2021 for other examples of combining Bayesian modeling with ACT-R cognitive models; see Weaver, 2008 ; Dotlačil, 2018 for arguments why this is necessary).…”
Section: Modeling Reading Datamentioning
confidence: 99%