title: Models of visual word recognition.
abstract: Reading is a complex process that draws on a remarkable number of diverse perceptual and cognitive processes. In this review, I provide an overview of computational models of reading, focussing on models of visual word recognition-how we recognise individual words. Early computational models had 'toy' lexicons, could simulate only a narrow range of phenomena, and frequently had fundamental limitations, such as being able to handle only four-letter words. The most recent models can use realistic lexicons, can simulate data from a range of tasks, and can process words of different lengths. These models are the driving force behind much of the empirical work on reading. I discuss how the data have guided model development and, importantly, I also provide guidelines to help interpret and evaluate the contribution the models make to our understanding of how we read.
authors.affiliation: Medical Research Council Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge CB2 7EF, UK. Electronic address: dennis.norris@mrc-cbu.cam.ac.uk.
authors.forename: Dennis
authors.initials: D
authors.lastname: Norris
mesh_terms: D001499:Bayes Theorem; D005133:Eye Movements / Q000502:physiology; D006801:Humans; D008959:Models, Neurological; D010364:Pattern Recognition, Visual / Q000502:physiology*; D011932:Reading
keywords: computational modelling; lexical decision; reading; word recognition