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Advances in the computational study of language acquisition

M R Brent1

  • 1Department of Cognitive Science, Johns Hopkins University, Baltimore, MD 21218, USA. brent@jhu.edu

Cognition
|October 1, 1996
PubMed
Summary

Computational linguistics explores how children acquire language. This tutorial introduces autonomous bootstrapping, a novel within-domain strategy complementing cross-domain approaches for language learning.

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Area of Science:

  • Computational Linguistics
  • Developmental Psychology
  • Cognitive Science

Background:

  • Introduces computational approaches to child language acquisition.
  • Connects computational and behavioral studies within a unified theoretical framework.
  • Reviews key papers on word meaning and phonological acquisition.

Discussion:

  • Highlights "autonomous bootstrapping"—a novel within-domain learning strategy.
  • Contrasts autonomous bootstrapping with classical cross-domain bootstrapping hypotheses.
  • Explains how partial or uncertain linguistic knowledge aids input analysis.

Key Insights:

  • Autonomous bootstrapping enables language acquisition using information within a single linguistic domain.
  • Integrates insights from word meaning acquisition via selectional preferences.
  • Incorporates algorithms for setting grammatical parameters.

Outlook:

  • Suggests future research directions in computational language acquisition.
  • Emphasizes the accessibility of recent advances to the research community.
  • Positions computational studies within current theoretical debates in linguistics.

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