Bayesian Modeling of Word and Pseudo-Word Reading in a Single-Route Architecture

We extend a Bayesian model of visual word recognition into a model of reading aloud, by developing a phonological sub-model. We show that it can recover implicit grapheme-to-phoneme conversion via the lexicon. Moreover, attentional control yields global and serial recoding, showing that pseudo-words can be read without specialized conversion.