Knowledge and Learning in Natural Language

ISBN13: 9780199254149ISBN10: 0199254141 Hardback, 192 pages

Also available:

Paperback
Mar 2003,  In Stock

Price:

$165.00 (06)

Description

It is a simple observation that children make mistakes when they learn a language. Yet, to the trained eye, these mistakes are far from random; in fact, they closely resemble perfectly grammatical utterances by adults--who speak other languages. This type of error analysis suggests a novel view of language learning: children are born with a fixed set of hypotheses about language--Chomsky's Universal Grammar--and these hypotheses compete to match the child's ambient language in a Darwinian fashion. The book presents evidence for this perspective from the study of children's words and grammar, and how language changes over time.

Features

  • Provides conclusive evidence of an innate human language faculty.
  • Shows how language learning leads to language change.
  • Throws fresh light on how children acquire language.

Reviews

"According to Yang, many of today's irregular verbs are historical survivors of what were once systematic rules ... By neglecting this historical evidence Pinker mistakenly supposes that the irregular cases have to be memorized on a case-by-case basis, whereas according to Yang what has to be memorized is which rule applies. Yang strengthens his argument by bringing in evidence from other languages. Yang argues that these irregular patterns are rule-based and that the child's task is not to memorize plurals on a word-by-word basis, but to figure out which rule applies, to which set the noun belongs. If Yang is right, and I think he is, then Pinker's irregulars are not illustrations of the words-and-rules thesis, but the less-general-rules-and-more-general-rules thesis."--The New York Review of Books, John R Searle

Product Details

192 pages; 10 figures; ISBN13: 978-0-19-925414-9ISBN10: 0-19-925414-1

About the Author(s)

Charles Yang has been teaching computational linguistics and language acquisition at Yale since receiving his Ph.D. in computer science at MIT.

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