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Linguistic inferences without words.

Lyn Tieu1,2,3,4, Philippe Schlenker5,6,7, Emmanuel Chemla5,8

  • 1Office of the Pro Vice-Chancellor (Research and Innovation), Western Sydney University, Penrith NSW 2751, Australia; lyn.tieu@gmail.com.

Proceedings of the National Academy of Sciences of the United States of America
|April 26, 2019
PubMed
Summary
This summary is machine-generated.

Linguistic inferences like implicatures and presuppositions are not unique to language. Cognitive science shows these inference types can be learned from novel nonlinguistic gestures and animations, suggesting domain-general cognitive origins.

Keywords:
gestureiconicityimplicatureinferencepresupposition

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Area of Science:

  • Cognitive Science
  • Linguistics
  • Semantics

Background:

  • Contemporary semantics categorizes linguistic inferences based on conversational status and behavior in complex sentences.
  • This typology is often considered language-specific and lexically encoded.

Purpose of the Study:

  • To investigate whether the established typology of linguistic inferences is exclusive to language.
  • To explore the cognitive underpinnings of inference types beyond their lexical encoding.

Main Methods:

  • Utilized "composite" utterances combining words with novel nonlinguistic iconic representations (gestures, animations).
  • Assessed the ability to learn linguistic meanings and replicate inference types from these composite stimuli in a "one-shot learning" paradigm.

Main Results:

  • Successfully replicated four major inference types (implicatures, presuppositions, supplements, homogeneity) using gestures and animations.
  • Demonstrated "one-shot learning" of these inference types from nonlinguistic iconic representations.

Conclusions:

  • The typology of inferences is not solely specific to language or lexically encoded.
  • Domain-general cognitive algorithms likely underlie this inferential typology, applying to both linguistic and nonlinguistic information.