Something about "us": Learning first person pronoun systems

Mora Maldonado, Jennifer Culbertson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Languages partition semantic space into linguistic categories in systematic ways. In this study, we investigate a semantic space which has received sustained attention in theoretical linguistics: person. Person systems convey the roles entities play in the conversational context(i.e., speaker(s), addressee(s), other(s)). Like other linguistic category systems (e.g. color and kinship terms),not all ways of partitioning the person space are equally likely. We use an artificial language learning paradigm to test whether typological frequency correlates with learnability of person paradigms. We focus on first persons ystems (e.g., ‘I’ and ‘we’ in English), and test the predictions of a set of theories which posit a universal set of features (±exclusive, and ±minimal) to capture this space.Our results provide the first experimental evidence for feature-based theories of person systems
Original languageEnglish
Title of host publicationProceedings of the 41st Annual Meeting of the Cognitive Science Society
Place of PublicationMontral
PublisherCognitive Science Society
Pages749-755
Publication statusPublished - 27 Jul 2019

Keywords

  • artificial language learning
  • categorization
  • person systems
  • typology
  • linguistic universals

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