Day 2
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How can modern neural networks like large language models be useful to the field of language acquisition, and more broadly cognitive science, if they are not a priori designed to be cognitive models? As developments towards natural language understanding and generation have improved leaps and bounds, with models like GPT-4, the question of how they can inform our understanding of human language acquisition has re-emerged. This talk will try to address how AI models as objects of study can ind...
Judit Gervain will discuss the parallels and the differences between infant language acquisition and AI language learning, focusing on the early stages of language learning in infants. In particular, she will compare and contrast the type and amount of input infants and Large Language Models need to learn language, the learning trajectories, and the presence/absence of critical periods. She has used near-infrared spectroscopy (NIRS) as well as cross-linguistic behavioral studies to shed light...
Is the goal of language acquisition research to account for children’s behavior (their productions and performance on tests of comprehension) or their knowledge? A first step in either goal is to establish facts about children’s linguistic behavior at the beginning of combinatorial speech. Recent work in our laboratory investigates children’s productions between roughly 15 and 22 months and suggests a combination of structured and less-structured utterances in which structured utterances come...