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Johns Hopkins University
Homewood Campus
(410-516-5250/office phone)

COGNITIVE SCIENCE DEPARTMENT
COLLOQUIUM PRESENTATION

Thursday, February 19, 2009
3:45 p.m.

Dr. Elissa Newport

Brain and Cognitive Sciences and Linguistics
Rochester University


Statistical language learning: Computational and maturational constraints

In recent years a number of problems in the brain and cognitive sciences have been addressed through statistical approaches, hypothesizing that both humans and animals learn or adapt to their perceptual environments by tuning themselves to the statistics of incoming stimulation.  This type of approach has been controversial, however, in the field of language acquisition, where questions arise concerning the types of statistics that might be usefully computed to reveal the complex hierarchical structure of languages and the limits on statistical approaches to learning symbolic systems.  In this talk I will review studies in which we have shown that infants, young children, and adults can compute, online and with remarkable speed, such things as how consistently sounds co-occur, how frequently words occur in similar contexts, and the like, and can then utilize such statistics to find candidate words in a speech stream, discover grammatical categories, and acquire simple syntactic structure in miniature languages in the laboratory.

A major question is how to think about the broader picture of statistical learning: How many kinds of statistical computations can learners perform?  How are these computations organized, and how are they constrained?  Our recent research has shown maturational changes in the ways in which various types of statistical arrays are compiled into generalizations: children and adults differ in important ways, with children sharpening the statistics and producing a more systematic and regular language than the one to which they are exposed.  These sharpening processes are also an important part of statistical learning, potentially explaining not only why children acquire language (and other patterns) more effectively than adults, but also how systematic languages may emerge in communities where usages are varied and inconsistent.  Overall the results of these studies suggest that a suitably sophisticated statistical learning mechanism may provide an account of a number of important aspects of language acquisition and structure. 


Cognitive Science Department
Johns Hopkins University
Room 237 Krieger Hall
3400 North Charles Street
Baltimore, MD 21218
Telephone: 410-516-5250
Fax: 410-516-8020

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