Uncertainty reduction as a measure of cognitive processing effort

Authors:
Stefan L. Frank
Affiliations:
University of Amsterdam, Amsterdam, The Netherlands
Venue:
CMCL '10 Proceedings of the 2010 Workshop on Cognitive Modeling and Computational Linguistics
Year:
2010

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Abstract

The amount of cognitive effort required to process a word has been argued to depend on the word's effect on the uncertainty about the incoming sentence, as quantified by the entropy over sentence probabilities. The current paper tests this hypothesis more thoroughly than has been done before by using recurrent neural networks for entropy-reduction estimation. A comparison between these estimates and word-reading times shows that entropy reduction is positively related to processing effort, confirming the entropy-reduction hypothesis. This effect is independent from the effect of surprisal.