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Cognitive Aspects of Computational Language Acquisition pp 1–25Cite as

Computational Modeling as a Methodology for Studying Human Language Learning

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Abstract

The nature and amount of information needed for learning a natural language, and the underlying mechanisms involved in this process, are the subject of much debate: how is the knowledge of language represented in the human brain? Is it possible to learn a language from usage data only, or is some sort of innate knowledge and/or bias needed to boost the process? Are different aspects of language learned in order? These are topics of interest to (psycho)linguists who study human language acquisition, as well as to computational linguists who develop the knowledge sources necessary for large-scale natural language processing systems. Children are the ultimate subjects of any study of language learnability. They learn language with ease, in a short period of time and their acquired knowledge of language is flexible and robust.

Excerpts of this chapter have been published in Alishahi, A. (2010), Computational Modeling of Human Language Acquisition, Synthesis Lectures on Human Language Technologies, Morgan & Claypool Publishers [2].

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Notes

  1. 1.

    On the other hand, it has been suggested that the language learner can estimate the “typical” rate of generalization for each syntactic form, whose distribution serves as “indirect” negative evidence [15, 42].

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Author information

Authors and Affiliations

  1. Laboratoire Langues, Textes, Traitements informatiques, Cognition, CNRS, Ecole Normale Supérieure and Université Sorbonne Nouvelle, Paris, France

    Thierry Poibeau

  2. Institute of Informatics, Federal University of Rio Grande do Sul, Av. Bento Gonçalves, 9500, Porto Alegre, Brazil

    Aline Villavicencio

  3. Computer Laboratory, University of Cambridge, Cambridge, CB3 0FD, UK

    Anna Korhonen

  4. Department of Theoretical and Applied Linguistics (DTAL), Cambridge, CB3 9DB, UK

    Anna Korhonen

  5. Department of Communication and Information Studies, Tilburg University, Tilburg, The Netherlands

    Afra Alishahi

Authors
  1. Thierry Poibeau
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  2. Aline Villavicencio
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  3. Anna Korhonen
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  4. Afra Alishahi
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Correspondence to Thierry Poibeau .

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Editors and Affiliations

  1. Institute of Informatics, Federal University of Rio Grande do Sul, Av. Bento Gonçalves, Porto Alegre, 9500, Brazil

    Aline Villavicencio

  2. Universite Sorbonne Nouvelle, LATTICE-CNRS, Ecole Normale Superieure and, rue d'Ulm 45, Paris, 75005, France

    Thierry Poibeau

  3. Computer Laboratory, William Gates Building, University of Cambridge, Thomson Avenue 15 JJ, Cambridge, CB3 0FD, United Kingdom

    Anna Korhonen

  4. and Communication (TiCC), Tilburg University, Tilburg center for Cognition, Warandelaan 2, Tilburg, 5037, Netherlands

    Afra Alishahi

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Poibeau, T., Villavicencio, A., Korhonen, A., Alishahi, A. (2013). Computational Modeling as a Methodology for Studying Human Language Learning. In: Villavicencio, A., Poibeau, T., Korhonen, A., Alishahi, A. (eds) Cognitive Aspects of Computational Language Acquisition. Theory and Applications of Natural Language Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31863-4_1

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