Settling Into Semantic Space: An Ambiguity-Focused Account of Word-Meaning Access.

Most words are ambiguous: Individual word forms (e.g., run) can map onto multiple different interpretations depending on their sentence context (e.g., the athlete/politician/river runs). Models of word-meaning access must therefore explain how listeners and readers can rapidly settle on a single, contextually appropriate meaning for each word that they encounter. I present a new account of word-meaning access that places semantic disambiguation at its core and integrates evidence from a wide variety of experimental approaches to explain this key aspect of language comprehension. The model has three key characteristics. (a) Lexical-semantic knowledge is viewed as a high-dimensional space; familiar word meanings correspond to stable states within this lexical-semantic space. (b) Multiple linguistic and paralinguistic cues can influence the settling process by which the system resolves on one of these familiar meanings. (c) Learning mechanisms play a vital role in facilitating rapid word-meaning access by shaping and maintaining high-quality lexical-semantic knowledge throughout the life span. In contrast to earlier models of word-meaning access, I highlight individual differences in lexical-semantic knowledge: Each person's lexicon is uniquely structured by specific, idiosyncratic linguistic experiences.