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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Do They Know It's Christmash? Lexical Knowledge Directly Impacts Speech Perception.

Sahil Luthra1, Anne Marie Crinnion2, David Saltzman2

  • 1Department of Psychology, Carnegie Mellon University.

Cognitive Science
|May 22, 2024
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Summary
This summary is machine-generated.

Lexical knowledge influences speech perception, supporting interactive cognitive models. This study refutes counter-arguments, reinforcing the role of top-down feedback in processing.

Keywords:
Computational modelFeedbackLanguageSpeech perceptionTop‐down effects

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Area of Science:

  • Cognitive Science
  • Psycholinguistics
  • Speech Perception

Background:

  • Lexically mediated compensation for coarticulation (LCfC) demonstrates how word knowledge impacts early speech processing.
  • LCfC evidence supports interactive cognitive models with top-down feedback loops.
  • Autonomous models, allowing only feedforward processing, are challenged by LCfC findings.

Discussion:

  • This work addresses counter-arguments challenging the interpretation of LCfC.
  • The analysis reaffirms that LCfC is a robust phenomenon.
  • The most parsimonious explanation for LCfC involves top-down feedback.

Key Insights:

  • Lexical effects on prelexical speech processing are replicable.
  • Interactive models of cognition are better supported than autonomous ones.
  • Top-down feedback is crucial for understanding LCfC.

Outlook:

  • Further research should explore the precise mechanisms of top-down feedback in LCfC.
  • Investigating LCfC across different languages and populations will enhance generalizability.
  • This research contributes to the broader debate on cognitive architecture and information flow.