ABSTRACT
This paper outlines a bottom-up research approach to studying lexical representation, emphasizing the development of infant phonological perception as a source of data that can illuminate the nature of phonological representations. It is proposed that neural network formalisms can provide a useful framework for thinking about these issues. We identify a key set of empirical results, understanding of which would yield considerable insight; this defines a modeling agenda for investigation of phonological representations. We report preliminary simulations that explore this agenda, exemplifying how network modeling techniques can contribute to understanding of these phenomena.
