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Related Experiment Videos

Competition and segmentation in spoken-word recognition

D Norris1, J M McQueen, A Cutler

  • 1Medical Research Council (MRC), Applied Psychology Unit, Cambridge, United Kingdom.

Journal of Experimental Psychology. Learning, Memory, and Cognition
|September 1, 1995
PubMed
Summary
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Listeners easily identify words in speech due to a model combining lexical competition and prosodic structure sensitivity. This spoken-word recognition ability balances word candidate competition with metrical segmentation for accurate word identification.

Area of Science:

  • Psycholinguistics
  • Computational Linguistics
  • Auditory Perception

Background:

  • Listeners identify words in continuous speech despite limited boundary cues.
  • Spoken-word recognition models are crucial for understanding auditory processing.

Purpose of the Study:

  • To investigate how listeners identify words in continuous speech.
  • To evaluate a model integrating lexical competition and prosodic structure.

Main Methods:

  • A word-spotting experiment was conducted.
  • Simulations using a computational model (Shortlist with Metrical Segmentation Strategy) were performed.
  • A lexicon of over 25,000 words was utilized.

Main Results:

  • Prosodic effects were most evident with high lexical competition.

Related Experiment Videos

  • Lexical competition modulates the impact of prosodic structure on word recognition.
  • The model accurately simulated experimental findings.

    • Conclusions:

    • Spoken-word recognition relies on both lexical competition and prosodic structure.
    • Integrating the Metrical Segmentation Strategy into the Shortlist model provides a robust account of word recognition.
    • Auditory processing effectively combines bottom-up (lexical) and top-down (prosodic) information.