Network Structure Influences Speech Production

Abstract

Network science provides a new way to look at old questions in cognitive science by examining the structure of a complex system, and how that structure might influence processing. In the context of psycholinguistics, clustering coefficient-a common measure in network science-refers to the extent to which phonological neighbors of a target word are also neighbors of each other. The influence of the clustering coefficient on spoken word production was examined in a corpus of speech errors and a picture-naming task. Speech errors tended to occur in words with many interconnected neighbors (i.e., higher clustering coefficient). Also, pictures representing words with many interconnected neighbors (i.e., high clustering coefficient) were named more slowly than pictures representing words with few interconnected neighbors (i.e., low clustering coefficient). These findings suggest that the structure of the lexicon influences the process of lexical access during spoken word production.