Let’s talk (efficiently) about us: Person systems achieve near-optimal compression

Noga Zaslavsky, Mora Maldonado, Jennifer Culbertson

Research output: Contribution to conferencePaperpeer-review

Abstract

Systems of personal pronouns (e.g.,‘you’ and ‘I’) vary widely across languages, but at the same time not all possible systems are attested. Linguistic theories have generally accounted for this in terms of strong grammatical constraints, but recent experimental work challenges this view. Here, we take a novel approach to understanding personal pronoun systems by invoking a recent information-theoretic framework for semantic systems that predicts that languages efficiently compress meanings into forms. We find that a test set of cross-linguistically attested personal pronoun systems achieves near-optimal compression, supporting the hypothesis that efficient compression shapes semantic systems. Further, our best-fitting model includes an egocentric bias that favors a salient speaker representation, accounting for a well-known typological generalization of person systems (‘Zwicky’s Generalization’) without the need for a hard grammatical constraint.

Original languageEnglish (US)
Pages938-944
Number of pages7
StatePublished - 2021
Event43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021 - Virtual, Online, Austria
Duration: Jul 26 2021Jul 29 2021

Conference

Conference43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021
Country/TerritoryAustria
CityVirtual, Online
Period7/26/217/29/21

Keywords

  • efficient coding
  • information theory
  • person systems
  • pronouns
  • semantic typology

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction

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