Connectionist psycholinguistics: capturing the empirical data

Connectionist psycholinguistics is an emerging approach to modeling empiric al data on human language processing using connectionist computational arch itectures. For almost 20 years, connectionist models have increasingly been used to model empirical data across many areas of language processing. We critically review four key areas: speech processing, sentence processing, l anguage production, and reading aloud, and evaluate progress against three criteria: data contact, task veridicality, and input representativeness. Re cent connectionist modeling efforts have made considerable headway toward m eeting these criteria, although it is by no means clear whether connectioni st (or symbolic) psycholinguistics will eventually provide an integrated mo del of full-scale human language processing.