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Real language learning

  • Jerome A. Feldman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1433)

Abstract

Formal studies of learning abstract grammars have, for decades, yielded deep results, some practical applications and quite a lot of fun. But no one believes that children learn the grammar of their native language independent of meaning (semantics) and use (pragmatics). Recent results suggest that is now possible, although still very difficult, to build computational and formal models of how children learn language. This paper will review some recent developments in computational modeling of language acquisition and suggest how they might be extended to grammatical inference.

Keywords

Word Sense Grammatical Inference Construction Grammar Computer Science Division Stochastic Context Free Grammar 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Jerome A. Feldman
    • 1
  1. 1.ICSIBerkeleyUSA

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