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Related Experiment Videos

Disfluencies and human language comprehension.

Fernanda Ferreira1, Karl G D Bailey

  • 1Department of Psychology, Michigan State University, MI 48824-1117, USA. Fernanda@eyelab.msu.edu <Fernanda@eyelab.msu.edu>

Trends in Cognitive Sciences
|May 4, 2004
PubMed
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Human sentence comprehension efficiently handles spoken disfluencies like "uh" and "um" through a linguistically principled parsing system. This research highlights cognitive mechanisms as adaptations to real-world communication challenges.

Area of Science:

  • Psycholinguistics
  • Computational Linguistics
  • Cognitive Science

Background:

  • Spoken language is characterized by disfluencies, including editing terms (e.g., "uh", "um"), repetitions, and corrections.
  • The study of how the human sentence comprehension system processes these disfluencies has gained significant traction in recent years.

Purpose of the Study:

  • To explore the empirical findings related to disfluency processing in human sentence comprehension.
  • To present a computational model that explains how disfluencies impact parsing and comprehension.
  • To investigate the adaptive nature of cognitive mechanisms in handling real-world communication.

Main Methods:

  • Review of empirical findings on spoken language disfluencies.
  • Description of a computational model for parsing and comprehension of disfluent speech.

Related Experiment Videos

  • Analysis of the efficiency and linguistic principles underlying disfluency handling.

    • Main Results:

    • The human sentence comprehension system, specifically the parser, efficiently processes disfluencies.
    • Disfluency handling by the parser is linguistically principled, suggesting an evolutionary adaptation for conversation.
    • The model captures the influence of disfluencies on parsing and comprehension.

    Conclusions:

    • Cognitive mechanisms, like sentence parsing, are adaptations to real-world communication constraints.
    • The efficient and principled handling of disfluencies demonstrates the adaptive nature of the human language processing system.
    • This research supports the view of cognitive functions as evolved solutions to environmental challenges.