CLS Speaker Series - Federica Bulgarelli (Penn State University) Double trouble: Statistical learning of multiple structures
Double trouble: Statistical learning of multiple structures
How do naïve learners come to identify the number of languages they are learning? This question is central to the study of language acquisition, but to date our understanding is far from complete. One means of approaching this problem is through the study of statistical learning, the process by which learners track rudimentary distributional information from their sensory input. For the past two decades, research has established that statistical learning is particularly critical for early language acquisition, allowing learners of all languages to gain a foothold into acquisition from which language-specific properties emerge. Research in our lab aims at broadening the scope of statistical learning tasks to understand how statistical learning might operate when learners are exposed to multiple underlying structures, arguably more closely approximating bilingual language acquisition. During this talk, I will discuss previous and ongoing studies that have focused on how learners across the lifespan and from different linguistic backgrounds detect shifts in patterns of speech streams as well as contend with multiple statistical regularities and rules.