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Neural Network Models for Language Acquisition: A Brief Survey

  • Jordi Poveda
  • Alfredo Vellido
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4224)

Abstract

Since the outbreak of connectionist modelling in the mid eighties, several problems in natural language processing have been tackled by employing neural network-based techniques. Neural network’s “biological plausibility” offers a promising framework in which the computational treatment of language may be linked to other disciplines such as cognitive science and psychology. With this brief survey, we set out to explore the landscape of artificial neural models for the acquisition of language that have been proposed in the research literature.

Keywords

Neural Network Model Natural Language Processing Language Acquisition Connectionist Model Lexical Category 
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 2006

Authors and Affiliations

  • Jordi Poveda
    • 1
  • Alfredo Vellido
    • 2
  1. 1.TALP Research Center 
  2. 2.Soft Computing Research GroupTechnical University of Catalonia (UPC)BarcelonaSpain

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