Proceedings of the Annual Meeting of the Cognitive Science Society

Children exploit regular links between the meanings of wordsand the syntactic structures in which they appear to learn aboutnovel words. This phenomenon, known as syntactic bootstrap-ping, is thought to play a critical role in word learning, espe-cially for words with more opaque meanings such as verbs.We present a computational word learning model which re-produces such syntactic bootstrapping phenomena after expo-sure to a naturalistic word learning dataset, even when undersubstantial memory constraints. The model demonstrates howexperimental syntactic bootstrapping effects constitute rationalbehavior given the nature of natural language input. The modelunifies computational accounts of word learning and syntacticbootstrapping effects observed in the laboratory, and offers apath forward for demonstrating the broad power of the syntax–semantics link in language acquisition.