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Garden-path effects in reading are not fully explained by surprisal alone. While surprisal predicts the existence of these reading slowdowns, it underestimates their magnitude and variation across sentence structures.

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Area of Science:

  • Psycholinguistics
  • Computational Linguistics
  • Cognitive Science

Background:

  • Syntactic ambiguity resolution can cause reading slowdowns (garden-path effects).
  • Previous models proposed reanalysis mechanisms for resolving ambiguity.
  • A recent proposal links garden-path effects to surprisal in a parallel parser.

Purpose of the Study:

  • To test the prediction that garden-path effects are proportional to the difference in word surprisal between competing interpretations.
  • To investigate whether predictability (surprisal) alone can account for syntactic disambiguation difficulty.

Main Methods:

  • Utilized recurrent neural network language models to calculate word-by-word surprisal for ambiguous sentences.
  • Measured human reading times using self-paced reading to estimate slowdowns attributed to surprisal.
  • Correlated surprisal estimates with syntactic disambiguation difficulty across constructions.

Main Results:

  • Surprisal successfully predicted the occurrence of garden-path effects.
  • Surprisal significantly underpredicted the magnitude of these reading slowdowns.
  • Surprisal failed to account for the varying severity of garden-path effects across different sentence types.

Conclusions:

  • Predictability, as measured by surprisal, is insufficient to fully explain syntactic disambiguation difficulty.
  • Reading comprehension likely involves additional mechanisms beyond predictability, such as reanalysis processes.
  • Further research is needed to integrate predictability with other cognitive mechanisms for a comprehensive model of reading.