The effect of word predictability on reading time is logarithmic
Open accessAbstract
It is well known that real-time human language processing is highly incremental and context-driven, and that the strength of a comprehender's expectation for each word encountered is a key determinant of the difficulty of integrating that word into the preceding context. In reading, this differential difficulty is largely manifested in the amount of time taken to read each word. While numerous studies over the past thirty years have shown expectation-based effects on reading times driven by lexical, syntactic, semantic, pragmatic, and other information sources, there has been little progress in establishing the quantitative relationship between expectation (or prediction) and reading times. Here, by combining a state-of-the-art computational language model, two large behavioral data-sets, and non-parametric statistical techniques, we establish for the first time the quantitative form of this relationship, finding that it is logarithmic over six orders of magnitude in estimated predictability. This result is problematic for a number of established models of eye movement control in reading, but lends partial support to an optimal perceptual discrimination account of word recognition. We also present a novel model in which language processing is highly incremental well below the level of the individual word, and show that it predicts both the shape and time-course of this effect. At a more general level, this result provides challenges for both anticipatory processing and semantic integration accounts of lexical predictability effects. And finally, this result provides evidence that comprehenders are highly sensitive to relative differences in predictability - even for differences between highly unpredictable words - and thus helps bring theoretical unity to our understanding of the role of prediction at multiple levels of linguistic structure in real-time language comprehension.
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A human's ease of processing a sentence is influenced by that sentence's probability.
“a human’s ease of processing a sentence is influenced by that sentence’s probability (66–68)”
From Embers of autoregression show how large language models are shaped by the problem they are trained to solve (2024) · cites this paper as [67]
The Discussion reports that word predictability affects word comprehension in context, and the paper relates that effect to reading time. It does not establish that the probability of an entire sentence affects how easily a human processes that sentence; its measured probabilities are for words in context. (LLM, conf=0.86)
Experimental — accuracy not yet measured
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- Authors
- Smith, N. J., & Levy, R.
- Affiliations
- University of California San Diego (US)
- Corresponding author
- Smith, Nathaniel J.
- ORCID
- Smith, Nathaniel J.
- Venue
- Cognition
- Publisher
- Elsevier BV
- Published
- 2013-09
- Volume
- 128
- Issue
- 3
- Pages
- 302-319
- ISSN
- 0010-0277 (ISSN-L)
- PMC
- PMC3709001
- OpenAlex
- W2108010971
- Cited by
- 725
- References
- 93
- Citations by year
- 2026: 61 · 2025: 84 · 2024: 46 · 2023: 80 · 2022: 60 · 2021: 74 · 2020: 52 · 2019: 91 · 2018: 50 · 2017: 29 · 2016: 36 · 2015: 34 · 2014: 17 · 2013: 10
- FWCI
- 66.84
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Cognition (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Science Foundation (T32-DC000041, 0953870)
- European Commission (270273)
- National Institutes of Health (0953870, T32-MH20002, HD065829, DC000041)
- National Institute of Mental Health (T32MH020002)
- National Institute on Deafness and Other Communication Disorders (T32DC000041)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD065829)
- FP7 Information and Communication Technologies
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Social Sciences › Psychology › Developmental and Educational Psychology › Second Language Acquisition and Learning
- Keywords
- word predictability, reading time, lexical predictability, anticipatory processing, oculomotor control, word recognition, semantic integration, real-time language comprehension
- MeSH terms
- Adult, Attention, Humans, Language, Reaction Time, Reading, Time Factors, Vocabulary, Recognition, Psychology, Comprehension
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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