Word learning emerges from the interaction of online referent selection and slow associative learning.

ABSTRACT: Classic approaches to word learning emphasize referential ambiguity: In naming situations, a novel word could refer to many possible objects, properties, actions, and so forth. To solve this, researchers have posited constraints, and inference strategies, but assume that determining the referent of a novel word is isomorphic to learning. We present an alternative in which referent selection is an online process and independent of long-term learning. We illustrate this theoretical approach with a dynamic associative model in which referent selection emerges from real-time competition between referents and learning is associative (Hebbian). This model accounts for a range of findings including the differences in expressive and receptive vocabulary, cross-situational learning under high degre

SUBMITTER: McMurray B 

PROVIDER: S-EPMC3632668 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature