Journal Article

Cognitive models of discourse comprehension for narrative generation

James Niehaus and R. Michael Young

in Literary and Linguistic Computing

Published on behalf of EADH: The European Association for Digital Humanities

Volume 29, issue 4, pages 561-582
Published in print December 2014 | ISSN: 0268-1145
Published online October 2014 | e-ISSN: 1477-4615 | DOI: https://dx.doi.org/10.1093/llc/fqu056
Cognitive models of discourse comprehension for narrative generation

More Like This

Show all results sharing these subjects:

  • Computational Linguistics
  • Language Teaching and Learning
  • Bibliography
  • Digital Lifestyle
  • Information and Communication Technologies

GO

Show Summary Details

Preview

This article presents an approach to using cognitive models of narrative discourse comprehension to define an explicit computational model of a reader’s comprehension process during reading, predicting aspects of narrative focus and inferencing with precision. This computational model is employed in a narrative discourse generation system to select and sequence content from a partial plan representing story world facts, objects, and events, creating discourses that satisfy comprehension criteria. Cognitive theories of narrative discourse comprehension define explicit models of a reader’s mental state during reading. These cognitive models are created to test hypotheses and explain empirical results about reader comprehension, but do not often contain sufficient precision for implementation on a computer. Therefore, they have not previously been suitable for computational narrative generation. The results of three experiments are presented and discussed, exhibiting empirical support for the approach presented. This work makes a number of contributions that advance the state-of-the-art in narrative discourse generation: a formal model of narrative focus, a formal model of online inferencing in narrative, a method of selecting narrative discourse content to satisfy comprehension criteria, and both implementation and evaluation of these models.

Journal Article.  9181 words.  Illustrated.

Subjects: Computational Linguistics ; Language Teaching and Learning ; Bibliography ; Digital Lifestyle ; Information and Communication Technologies

Full text: subscription required

How to subscribe Recommend to my Librarian

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content. subscribe or login to access all content.