Linguistic inferences without words

Lyn Tieu*, Philippe Schlenker, Emmanuel Chemla

*Corresponding author for this work

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Contemporary semantics has uncovered a sophisticated typology of linguistic inferences, characterized by their conversational status and their behavior in complex sentences. This typology is usually thought to be specific to language and in part lexically encoded in the meanings of words. We argue that it is neither. Using a method involving “composite” utterances that include normal words alongside novel nonlinguistic iconic representations (gestures and animations), we observe successful “one-shot learning” of linguistic meanings, with four of the main inference types (implicatures, presuppositions, supplements, homogeneity) replicated with gestures and animations. The results suggest a deeper cognitive source for the inferential typology than usually thought: Domain-general cognitive algorithms productively divide both linguistic and nonlinguistic information along familiar parts of the linguistic typology.

Original languageEnglish
Pages (from-to)9796-9801
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume116
Issue number20
DOIs
Publication statusPublished - 14 May 2019

Keywords

  • gesture
  • inference
  • implicature
  • presupposition
  • iconicity

Fingerprint Dive into the research topics of 'Linguistic inferences without words'. Together they form a unique fingerprint.

  • Cite this