This Special Issue on Connectionist Models of Human Language Processing provides an opportunity for an appraisal both of specific connectionist models and of the status and utility of connectionist models of language in general. This introduction provides the background for the papers in the Special Issue. The development of connectionist models of language is traced, from their intellectual origins, to the state of current research. Key themes that arise throughout different areas of connectionist psycholinguistics are highlighted, and recent developments in (...) speech processing, morphology, sentence processing, language production, and reading are described. We argue that connectionist psycholinguistics has already had a significant impact on the psychology of language, and that connectionist models are likely to have an important influence on future research. (shrink)

A critical property of the perception of spoken words is the transient ambiguity of the speech signal. In localist models of speech perception this ambiguity is captured by allowing the parallel activation of multiple lexical representations. This paper examines how a distributed model of speech perception can accommodate this property. Statistical analyses of vector spaces show that coactivation of multiple distributed representations is inherently noisy, and depends on parameters such as sparseness and dimensionality. Furthermore, the characteristics of coactivation vary considerably, (...) depending on the organization of distributed representations within the mental lexicon. This view of lexical access is supported by analyses of phonological and semantic word representations, which provide an explanation of a recent set of experiments on coactivation in speech perception (Gaskell & Marslen–Wilson, 1999). (shrink)