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Examining Online Syntactic Processing of Spoken Complex Sentences in Chinese Using Dual-Modal Interference Tasks
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Linguistic experience and processing speed differentially affect lexical retrieval and structural assembly during

Florian Hintz1,2,3, Mohammad Momenian4

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Linguistic experience aids word retrieval, while processing speed and working memory influence sentence construction complexity. This study reveals how these factors interact in language production.

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Individual differencesLanguage productionProcessing speed

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Area of Science:

  • Cognitive Psychology
  • Psycholinguistics
  • Neuroscience

Background:

  • Language production involves lexical retrieval and structural assembly.
  • Domain-general skills support these processes.
  • Individual differences in these skills impact language abilities.

Purpose of the Study:

  • To investigate how linguistic experience and domain-general skills jointly affect language production.
  • To examine these effects across different levels of linguistic complexity.
  • To understand the cognitive architecture of language production through an individual-differences approach.

Main Methods:

  • 169 participants completed picture naming, phrase generation, and sentence generation tasks.
  • Participants underwent 15 tests measuring linguistic experience, processing speed, working memory, and nonverbal reasoning.
  • Speech onset latencies and durations were analyzed.

Main Results:

  • Linguistic experience correlated with faster speech initiation, especially in picture naming (lexical access).
  • Processing speed predicted earlier speech initiation and shorter durations, particularly for complex structures (structural assembly).
  • Working memory influenced planning distribution, affecting onset latencies and durations.

Conclusions:

  • Linguistic experience, processing speed, and working memory play distinct roles in language production.
  • Processing speed is crucial for real-time structural assembly under time constraints.
  • A holistic individual-differences approach offers valuable insights into language production mechanisms.