Large-scale evidence for logarithmic effects of word predictability on reading time
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Open access
Date
2024-03-05Type
- Journal Article
Abstract
During real-time language comprehension, our minds rapidly decode complex meanings from sequences of words. The difficulty of doing so is known to be related to words' contextual predictability, but what cognitive processes do these predictability effects reflect? In one view, predictability effects reflect facilitation due to anticipatory processing of words that are predictable from context. This view predicts a linear effect of predictability on processing demand. In another view, predictability effects reflect the costs of probabilistic inference over sentence interpretations. This view predicts either a logarithmic or a superlogarithmic effect of predictability on processing demand, depending on whether it assumes pressures toward a uniform distribution of information over time. The empirical record is currently mixed. Here, we revisit this question at scale: We analyze six reading datasets, estimate next-word probabilities with diverse statistical language models, and model reading times using recent advances in nonlinear regression. Results support a logarithmic effect of word predictability on processing difficulty, which favors probabilistic inference as a key component of human language processing. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000666108Publication status
publishedExternal links
Journal / series
Proceedings of the National Academy of Sciences of the United States of AmericaVolume
Pages / Article No.
Publisher
National Academy of SciencesSubject
language; prediction; reading; nonlinear regression; human language processingOrganisational unit
02150 - Dep. Informatik / Dep. of Computer Science
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