Edited by Inbal Arnon and Eve V. Clark
[Trends in Language Acquisition Research 7] 2011
► pp. 153–166
Two- and three-year-olds' linguistic generalizations are prudent adaptations to the language they hear
Studies of children's “statistical learning” mechanisms have established that even infants are very competent at extracting grammar-like structure from sequences of language-like sounds. We review some recent work exploring how these mechanisms might be used to extract functional grammatical knowledge from real speech. We use statistical analysis of large samples of transcribed child-directed speech to make predictions about the generalizations children will make, which we then test in the lab. We provide evidence that children's generalizations are input-driven: they are more likely to be made not only where the input gives supporting evidence, but also where the input gives no opportunity for concrete reuse and thus pushes the child to make an inductive inference. Keywords: Statistical learning; child-directed speech; rational models
Cited by other publications
This list is based on CrossRef data as of 20 september 2020. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.