Real words, phantom words and impossible words

Abstract

Because spoken language arrives as a continuous signal, recognising words in real speech requires segmentation of the speech stream. Current computational models of spoken-word recognition involve a competition process which assists with segmentation without requiring explicit word-boundary knowledge. Studies of vocabulary structure and of a real-speech corpus will be described which show that English encourages competition; most words have "phantom" words embedded within them. Experimental evidence will be presented supporting the claim that spoken-word recognition by human listeners involves such active competition between candidate words, but also the exploitation of cues to segmentation, and moreover that listeners are sensitive to what could and could not be a possible word of their language. This latter constraint on the recognition words can be incorporated into a competition model of spoken-word recognition, and provides a simple and powerful account of a range of empirical data.