Connectionist psycholinguistics: capturing the empirical data

Connectionist psycholinguistics is an emerging approach to modeling empirical data on human language processing using connectionist computational architectures. 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, language production, and reading aloud, and evaluate progress against three criteria: data contact, task veridicality, and input representativeness. Recent connectionist modeling efforts have made considerable headway toward meeting these criteria, although it is by no means clear whether connectionist (or symbolic) psycholinguistics will eventually provide an integrated model of full-scale human language processing.