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Updated: Jan 6, 2026

Examining Online Syntactic Processing of Spoken Complex Sentences in Chinese Using Dual-Modal Interference Tasks
Published on: September 5, 2019
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.
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.
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.
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