Computational models of language acquisition

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Child language acquisition, one of Nature's most fascinating phenomena, is to a large extent still a puzzle. Experimental evidence seems to support the view that early language is highly formulaic, consisting for the most part of frozen items with limited productivity. Fairly quickly, however, children find patterns in the ambient language and generalize them to larger structures, in a process that is not yet well understood. Computational models of language acquisition can shed interesting light on this process. This paper surveys various works that address language learning from data; such works are conducted in different fields, including psycholinguistics, cognitive science and computer science, and we maintain that knowledge from all these domains must be consolidated in order for a well-informed model to emerge. We identify the commonalities and differences between the various existing approaches to language learning, and specify desiderata for future research that must be considered by any plausible solution to this puzzle.

Original languageEnglish
Title of host publicationComputational Linguistics and Intelligent Text Processing - 11th International Conference, CICLing 2010, Proceedings
Number of pages14
StatePublished - 2010
Event11th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2010 - Iasi, Romania
Duration: 21 Mar 201027 Mar 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6008 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2010

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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