Psychological and Brain Sciences Spiker Memorial Lecture

Jenny Saffran, Rubenstein Professor, Department of Psychology, University of Wisconsin-Madison

Learning to Understand: Statistical Learning and Language

Abstract: Infants rapidly develop from being naïve listeners, who experience language as a sea of sounds, to understanding their native language(s). How does this remarkable learning process unfold? One potentially useful source of information lies in the statistical patterns that characterize natural languages, which signal structures ranging from phonemes to words to grammatical structures. Over the past two decades, researchers have demonstrated that infants are sensitive to myriad statistical regularities in language input. Beyond merely tracking these patterns, how might infants use statistical regularities to support language development? In my presentation, I will explore the hypothesis that infants exploit statistical regularities in the service of efficiently processing information in their linguistic environments. To this end, I will discuss studies from my lab examining the role of statistical learning in infants’ uncertainty reduction behaviors (including predictive processing, error-based learning, and active sampling). By learning to efficiently encode language input, infants become increasingly able to process their native language(s).