Statistical Learning of Language

Statistical learning is a contributing process in language acquisition. The central notion behind statistical learning comes from a blend of older ideas from structural linguistic and nativist perspectives, namely, that the distributional characteristics of natural language reflect underlying linguistic structure and that the development of language requires learning. Where present-day theories of statistical learning diverge from previous perspectives is in the nature of the mechanisms hypothesized for language acquisition. This article outlines the fundamental challenge of language acquisition and reviews recent findings which suggest that infants (and adults) are able to track statistical information in linguistic input and that they may be able to use that information for phonetic acquisition, speech segmentation, word learning, and acquisition of simple grammatical structure. These statistical learning mechanisms appear to be both powerful and constrained, and they function across domains, modalities, and species.