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Discriminating Local and Distributed Models of Competition in Spoken Word Recognition
Abstract
Local and distributed theories of representation make different predictions regarding the simultaneous activation of multiple lexical entries during speech perception. We report three experiments that use the cross-modal priming technique with fragments of spoken words to explore competition effects in the activation of multiple lexical representations. The experiments suggest that lexical activation is inversely related to the number of words being activated. This competition effect is stronger at the semantic than the phonological level of representation, supporting a model of speech perception in which sensory information is mapped directly onto distributed representations of both the form and the meanings of words.
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