A model of local coherence effects in human sentence processing as consequences of updates from bottom-up prior to posterior beliefs

Klinton Bicknell*, Roger Levy

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Human sentence processing involves integrating probabilistic knowledge from a variety of sources in order to incrementally determine the hierarchical structure for the serial input stream. While a large number of sentence processing effects have been explained in terms of comprehenders' rational use of probabilistic information, effects of local coherences have not. We present here a new model of local coherences, viewing them as resulting from a belief-update process, and show that the relevant probabilities in our model are calculable from a probabilistic Earley parser. Finally, we demonstrate empirically that an implemented version of the model makes the correct predictions for the materials from the original experiment demonstrating local coherence effects.

Original languageEnglish (US)
Title of host publicationNAACL HLT 2009 - Human Language Technologies
Subtitle of host publicationThe 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Proceedings of the Conference
Pages665-673
Number of pages9
StatePublished - Dec 1 2009
EventHuman Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, NAACL HLT 2009 - Boulder, CO, United States
Duration: May 31 2009Jun 5 2009

Other

OtherHuman Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, NAACL HLT 2009
CountryUnited States
CityBoulder, CO
Period5/31/096/5/09

ASJC Scopus subject areas

  • Language and Linguistics
  • Social Sciences (miscellaneous)

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    Bicknell, K., & Levy, R. (2009). A model of local coherence effects in human sentence processing as consequences of updates from bottom-up prior to posterior beliefs. In NAACL HLT 2009 - Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Proceedings of the Conference (pp. 665-673)