Children's Acquisition of Syntax: Simple Models are Too Simple<sup>*</sup>

Xuan‐Nga Cao Kam and Janet Dean Fodor

in Rich Languages From Poor Inputs

Published in print December 2012 | ISBN: 9780199590339
Published online January 2013 | e-ISBN: 9780191745041 | DOI:
Children's Acquisition of Syntax: Simple Models are Too Simple*

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This chapter examines the prospects for n-gram-based learning of natural language syntax. It finds that low-level statistics over word strings might contribute to syntax learning but cannot substitute for syntactic knowledge. Such statistics cannot capture the generalization about auxiliary inversion. Theoretical differences aside, the only route to the correct generalization requires a bias toward local syntactic dependencies, defined over a phrase structure analysis of the sentence. Hence, a learner that makes use of word-level statistics as the basis for auxiliary inversion must, at a minimum, also have an innate propensity to project phrase structure onto word strings, just as Noam Chomsky observed four decades ago.

Keywords: language acquisition; natural language; language syntax; language learning; word-level statistics; word strings; auxiliary inversion

Chapter.  8301 words.  Illustrated.

Subjects: Linguistics

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