Lossy‐Context Surprisal: An Information‐Theoretic Model of Memory Effects in Sentence Processing
Name
cogs.12814.pdf
Description
Published version
Size
2.52 MB
Format
Adobe PDF
Checksum (MD5)
6f3e3584d9a383286f1a5e61f9be44e0
Author(s)
Futrell, Richard
Gibson, Edward
Levy, Roger P
Date Issued
2020
Journal
Cognitive Science
Publisher
Wiley
Version
Final published version
Abstract
Copyright © 2020 The Authors. Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society (CSS) A key component of research on human sentence processing is to characterize the processing difficulty associated with the comprehension of words in context. Models that explain and predict this difficulty can be broadly divided into two kinds, expectation-based and memory-based. In this work, we present a new model of incremental sentence processing difficulty that unifies and extends key features of both kinds of models. Our model, lossy-context surprisal, holds that the processing difficulty at a word in context is proportional to the surprisal of the word given a lossy memory representation of the context—that is, a memory representation that does not contain complete information about previous words. We show that this model provides an intuitive explanation for an outstanding puzzle involving interactions of memory and expectations: language-dependent structural forgetting, where the effects of memory on sentence processing appear to be moderated by language statistics. Furthermore, we demonstrate that dependency locality effects, a signature prediction of memory-based theories, can be derived from lossy-context surprisal as a special case of a novel, more general principle called information locality.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Creative Commons Attribution NonCommercial License 4.0
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DOI of Published Version
https://doi.org/10.1111/COGS.12814
