Cognitively Plausible Models of Human Language Processing

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


We pose the development of cognitively
plausible models of human language processing
as a challenge for computational
linguistics. Existing models can only deal
with isolated phenomena (e.g., garden
paths) on small, specifically selected data
sets. The challenge is to build models that
integrate multiple aspects of human language
processing at the syntactic, semantic,
and discourse level. Like human language
processing, these models should be
incremental, predictive, broad coverage,
and robust to noise. This challenge can
only be met if standardized data sets and
evaluation measures are developed.
Original languageEnglish
Title of host publicationACL 2010, Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, July 11-16, 2010, Uppsala, Sweden, Short Papers
Number of pages8
Publication statusPublished - 2010


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