Purpose The purpose of this study was to differentiate effects of phonotactic probability, the likelihood of occurrence of a sound sequence, and neighborhood density, the number of words that sound similar to a given word, on adult word learning. A second purpose was to determine what aspect of word learning (viz., triggering learning, formation of an initial representation, or integration with existing representations) was influenced by each variable. Method Thirty-two adults were exposed to 16 nonwords paired with novel objects in a story context. The nonwords orthogonally varied in phonotactic probability and neighborhood density. Learning was measured following 1, 4, and 7 exposures in a picture-naming task. Partially correct (i.e., 2 of 3 phonemes correct) and completely correct responses (i.e., 3 of 3 phonemes correct) were analyzed together and independently to examine emerging and partial representations of new words versus complete and accurate representations of new words. Results Analysis of partially correct and completely correct responses combined showed that adults learned a lower proportion of high-probability nonwords than low-probability nonwords (i.e., high-probability disadvantage) and learned a higher proportion of high-density nonwords than low-density nonwords (i.e., high-density advantage). Separate analysis of partially correct responses yielded an effect of phonotactic probability only, whereas analysis of completely correct responses yielded an effect of neighborhood density only. Conclusions These findings suggest that phonological and lexical processing influence different aspects of word learning. In particular, phonotactic probability may aid in triggering new learning, whereas neighborhood density may influence the integration of new lexical representations with existing representations.

Phonotactic probability, neighborhood density, and onset density were manipulated in 4 picture-naming tasks. Experiment 1 showed that pictures of words with high phonotactic probability were named more quickly than pictures of words with low phonotactic probability. This effect was consistent over multiple presentations of the pictures (Experiment 2). Manipulations of phonotactic probability and neighborhood density showed only an influence of phonotactic probability (Experiment 3). In Experiment 4, pictures of words with sparse onsets were named more quickly than pictures of words with dense onsets. The results of these experiments provide additional constraints on the architecture and processes involved in models of speech production, as well as constraints on the connections between the recognition and production systems.

Phonotactic probability refers to the frequency with which segments and sequences of segments appear in a word or syllable. Neighborhood density refers to the number of words that are phonologically similar to a target word. These variables have been shown to influence word recognition, but little work has examined how these variables influence speech production. Although these two variables are positively correlated in English, words that varied orthogonally on these characteristics were selected and presented in a picture-naming task to assess the speed and accuracy of lexical retrieval during speech production. The results suggest that both facilitative and competitive processes operate during lexical retrieval in speech production. The implications for models of speech production are discussed. [Work funded by NIH-NIDCD R03 DC 04259.]

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Previous research has shown that the number of phonologically similar items influences the processing of spoken words (e.g., Vitevitch, 2002; Vitevitch and Luce, 1998). The present experiment examines the influence of semantic similarity on the speed and accuracy of spoken word recognition using a lexical decision task. Semantic density refers to the number of words that are semantically associated to a given word (Nelson, McEvoy, and Schreiber, 1998). A word that has relatively many semantically associated words has high semantic density and a word that has relatively few semantically associated words has low semantic density. The results showed that words with high semantic density were responded to more quickly and accurately than words with low semantic density, suggesting that semantic information influences spoken word recognition.

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