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Interaction in Spoken Word Recognition Models: Feedback Helps.

James S Magnuson1,2, Daniel Mirman3, Sahil Luthra1,2

  • 1Department of Psychological Sciences, University of Connecticut, Storrs, CT, United States.

Frontiers in Psychology
|April 19, 2018
PubMed
Summary
This summary is machine-generated.

Online feedback is crucial for human perception and cognition, especially in noisy conditions. Simulations show interactive activation models with feedback outperform those without, supporting the interactive activation hypothesis.

Keywords:
Bayesian modelscomputational modelspsycholinguisticssimulationsspeech perceptionspoken word recognition

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Area of Science:

  • Cognitive Science
  • Computational Neuroscience
  • Psychology

Background:

  • Human perception relies on integrating sensory input with prior knowledge.
  • The interactive activation hypothesis proposes bidirectional neural networks for this integration.
  • Debate exists on whether online feedback is necessary for efficient processing.

Purpose of the Study:

  • To test the necessity and benefit of online feedback in spoken word recognition models.
  • To evaluate the robustness of interactive activation models in noisy environments.
  • To critically assess arguments differentiating forms of online feedback.

Main Methods:

  • Simulations using the TRACE interactive activation model with and without feedback.
  • Testing with a large vocabulary of words under varying noise levels.
  • Review of theoretical arguments regarding online feedback mechanisms.

Main Results:

  • A majority of words were recognized faster with feedback than without.
  • Model performance (accuracy and speed) significantly improved with feedback in noisy conditions.
  • Simulations demonstrated the robustness benefits of feedback.

Conclusions:

  • Online feedback is beneficial for spoken word recognition, particularly in noise.
  • The interactive activation hypothesis is supported by the findings.
  • Online feedback plausibly implements various beneficial feedback mechanisms.