Towards a complete model of reading: Simulating lexical decision, word naming, and sentence reading with Über-Reader
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Open Access
Type
ArticleAbstract
This paper presents simulations of eye movements during reading, lexical decision, and naming using Über-Reader, a new computational model that aims to provide a complete account of the perceptual, cognitive, and motor processes involved in reading. The present simulations focused ...
See moreThis paper presents simulations of eye movements during reading, lexical decision, and naming using Über-Reader, a new computational model that aims to provide a complete account of the perceptual, cognitive, and motor processes involved in reading. The present simulations focused on Über-Reader’s word-identification module—an implemen-tation of the Multiple-Trace Memory model (Ans et al., 1998) based on the theoretical assumptions of the MI-NERVA 2 model of episodic memory (Hintzman, 1984)—with a vocabulary comprising the full corpus of the Eng-lish Lexicon Project (Balota et al., 2007). The model’s lex-icon was probed with words and one-letter-different non-words from the Schilling et al. (1998) corpus, and outputs of the model were scored to evaluate performance against the empirical data. The outcomes of these simulations will inform further development of Über-Reader by providing the foundation for our ultimate goal of simulating reading, in its entirety.
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See moreThis paper presents simulations of eye movements during reading, lexical decision, and naming using Über-Reader, a new computational model that aims to provide a complete account of the perceptual, cognitive, and motor processes involved in reading. The present simulations focused on Über-Reader’s word-identification module—an implemen-tation of the Multiple-Trace Memory model (Ans et al., 1998) based on the theoretical assumptions of the MI-NERVA 2 model of episodic memory (Hintzman, 1984)—with a vocabulary comprising the full corpus of the Eng-lish Lexicon Project (Balota et al., 2007). The model’s lex-icon was probed with words and one-letter-different non-words from the Schilling et al. (1998) corpus, and outputs of the model were scored to evaluate performance against the empirical data. The outcomes of these simulations will inform further development of Über-Reader by providing the foundation for our ultimate goal of simulating reading, in its entirety.
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Date
2020-01-01Source title
Proceedings of the 42nd Annual Conference of the Cognitive Science SocietyPublisher
Cognitive Science SocietyFunding information
ARC DP190100719Licence
Creative Commons Attribution 4.0Faculty/School
Faculty of Science, School of PsychologyShare