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Speakers balance their own knowledge with their listener's perspective when describing objects. This study models how both viewpoints influence language, finding listeners' perspectives are prioritized.

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Area of Science:

  • Cognitive Science
  • Psycholinguistics
  • Computational Linguistics

Background:

  • Speakers often adapt their language to their listener's knowledge state.
  • Egocentric biases in language production are also frequently observed.
  • A unified explanation for this mixed behavior is lacking.

Purpose of the Study:

  • To model the probabilistic combination of speaker and addressee perspectives in referring expression production.
  • To explain the observed "mixed" behavior in language use.

Main Methods:

  • A computational model was developed integrating both speaker and addressee perspectives.
  • A language production experiment was conducted with participants describing objects in a context with a visually misleading item.
  • Experimental conditions varied whether the misleading object's function was known to one or both participants.

Main Results:

  • Neither a purely egocentric nor a purely allocentric model could explain the experimental findings.
  • A model combining both perspectives successfully predicted the observed behavioral patterns.
  • Speakers weighted their addressee's perspective more heavily than their own.

Conclusions:

  • Referring expression production is influenced by a probabilistic combination of both speaker and addressee perspectives.
  • The model provides a computational account for mixed egocentric and allocentric behavior in language.
  • Understanding listener knowledge is crucial, with speakers prioritizing this information over their own in certain contexts.