McGILL UNIVERSITY DEPARTMENT OF LINGUISTICS AND SCHOOL OF COMPUTER SCIENCE
Language allows us to face novel concepts and situations by building structured mental representations of the world. The primary goal of my research program is to use computational models and behavioral experiments to understand how we construct and update these rich mental models both from experience (i.e., language acquisition) and from language (i.e., language processing). In this talk, I draw on methods in computational linguistics and computational cognitive science to propose a model of lexical acquisition formalized as logical program induction. First, I’ll illustrate how the model explains the systematic patterns of behavior observed in children as they acquire kinship words. Then, I will present a large cross-cultural data analysis model that infers how children use data from the timing of their lexical acquisition. Lastly, I will use children’s acquisition of exact number words as a case study to demonstrate how both of these models can be combined to learn about the universal and culturally-specific processes of the human learning machine. Taken together, this body of work provides the first computational model for how children learn relational word meanings, the first large-scale cross-linguistic model of children’s data usage during early word learning and an innovative computational toolbox for leveraging large datasets and discipline knowledge to draw theoretical insights in child development.