similar are closer to one another than to ones that are dissimilar, and exemplars that occur frequently are stronger than less frequent ones (Johnson 1997; Bybee 2000a, 2001; Pierrehumbert 2001). These exemplar clusters, which represent autonomous words, change as experience with language changes. Repeated exemplars within the cluster grow stronger, and less frequently used ones may fade over time, as other memories do.Changes in the phonetic range of the exemplar cluster may also take place as language is used and new tokens of words are experienced. Thus the range of phonetic variation of a word can gradually change over time, allowing a phonetically gradual sound change to affect different words at different rates. Given a tendency for reduction during production, the phonetic representation of a word will gradually accrue more exemplars that are reduced, and these exemplars will become more likely to be chosen for production, where they may undergo further reduction, gradually moving the words of the language in a consistent direction. The more frequent words will have more chances to undergo online reduction and thus will change more rapidly. The more predictable words (which are usually also the more frequent ones) will have a greater chance of having their reduced version chosen, given the context, and thus will advance the reductive change more rapidly.The exemplar clusters are embedded in a network of associations among words that map relations of similarity at all levels. Distinct words with similar phonetic properties are associated, as are words with shared semantic features. I have shown in (Bybee 1985, 1988) that morphemes and morphological relations in such a network emerge from parallel phonetic and semantic associations and that schemas or abstractions over relations of similarity can be formulated to account for the regularities and patterns evident in language use.(...)An important property of the exemplar model is the emphasis on words as storage units. Various models have proposed that even multi-morphemic words have lexical listing. Vennemann (1974) argued that appropriate constraints on syllable structure can only be applied to whole words, not to morphemes. The common objection to this proposal made in the 1970s was that the human brain does not have sufficient storage capacity for all the words of a language, especially a language with large morphological paradigms. This argument has now been dismissed with the discovery of the huge amount of detail that the brain is capable of recording. Moreover, newer conceptions of the lexicon, not as a list but as a network with tight interconnections, provide the insight that listing two related words, such as start, started, does not take up as much cognitive space as listing two unrelated words, such as start, flower (Bybee 1985). Thus connectionist models (Rumelhart and McClelland 1986) and analogical models (Skousen 1989, 1992; Eddington 2000) have storage of whole words with morphological relations emergent from the categorization involved in storage. In addition, the lexical diffusion data provide evidence that multi-morphemic words can have lexical storage. As we saw in table 11.3, high-frequency regular past-tense English verbs are more likely to have their final /t/ or /d/ deleted