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Decoding the implausible: Mandarin sentence interpretation through the noisy channel model.

Ruihua Mao1, Sihan Chen2, Edward Gibson2

  • 1Laboratoire de Linguistique Formelle, Université Paris Cité, Bât. Olympe de Gouges, 5ème étage, 8, Rue Albert Einstein, 75013, Paris, France. ruihua.mao@etu.u-paris.fr.

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Summary
This summary is machine-generated.

This study tested the noisy channel language comprehension model in Mandarin Chinese. Mandarin speakers made the most inferences for sentences with single morpheme errors, supporting the noisy channel hypothesis.

Keywords:
MandarinNoisy channelRational inferenceSentence processing

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Area of Science:

  • Psycholinguistics
  • Computational Linguistics
  • Cognitive Science

Background:

  • The noisy channel language comprehension proposal suggests readers identify and fix sentence interpretation errors.
  • Previous research (Zhan et al., 2023) explored this in English.

Purpose of the Study:

  • To test the noisy channel model's applicability to Mandarin Chinese.
  • To investigate how different syntactic structures influence error correction during language comprehension.

Main Methods:

  • Replication and extension of Zhan et al. (2023) using three Mandarin Chinese syntactic alternations.
  • Participants read implausible sentences and answered comprehension questions to gauge literal interpretation.

Main Results:

  • Mandarin speakers showed the highest inference rates for sentences with single morpheme deletions/insertions.
  • Inference rates decreased for noun phrase exchanges across function words, then across main verbs.
  • Results align with Zhan et al. (2023), confirming the noisy channel framework's robustness.

Conclusions:

  • The noisy channel framework effectively explains Mandarin Chinese language comprehension.
  • Language-specific properties significantly impact how comprehenders process and correct sentence errors.