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HAI Weekly Seminar with Michael Frank

Bigger Data About Smaller People: Investigating Children's Language Learning at Scale

Every typically developing child learns to talk, but children vary tremendously in how and when they do so. What predicts this variability? And which aspects of early language learning are consistent across the world’s languages and cultures? We use data from tens of thousands of children learning dozens of different languages to create a framework for building and evaluating predictive models of language development. 

Michael  Frank

Michael Frank

David and Lucile Packard Professor of Human Biology, and Director, Symbolic Systems Program. I study children's language learning and how it interacts with their developing understanding of the social world. I am interested in bringing larger datasets to bear on these questions and use a wide variety of methods including eye-tracking, tablet experiments, and computational models.