Empirical psychological experimentation (very briefly reviewed here) has provided evidence of top-down conceptual constraints on letter perception. The role hypothesis suggests that these conceptual constraints take the form of structural subcomponents (roles) and relations between subcomponents (r-roles). In this paper, we present a fully-implemented computer model based on the role hypothesis of letter recognition. The emergent model of letter perception discussed below offers a cogent explanation of human letter-perception data β especially with regard to error-making. The model goes beyond simple categorization by parsing a letter-form into its constituent parts. As it runs, the model dynamically builds (and destroys) a context-sensitive internal representation of the letter that it is perceiving. The representation emerges as by-product of a parallel exploration of possible categories. The model is able to successfully recognize (i.e., conceptually parse) many diverse letters at the extremes of their categories
