Production is biased to provide informative cues early: Evidence from miniature artificial languages

Maryia Fedzechkina, T. Florian Jaeger, John C. Trueswell

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

4 Scopus citations

Abstract

The role of processing constraints on sentence structure has been a topic of central interest in cognitive science. One proposal (Hawkins, 2004) suggests that language production system is organized to facilitate efficient parsing. We experimentally test this hypothesis using a miniature artificial language learning paradigm. Our findings support this account. Even though the input languages did not favor early placement of cues to grammatical function assignment (case and word order), participants used these cues in their own productions significantly more often in such a way as to allow early correct parsing commitments. This preference interacted with a bias to mark the less expected: Participants tended to use more case-marking in non-English OSV sentences. Our results underscore the potential of miniature artificial learning for language production research.

Original languageEnglish (US)
Title of host publicationProceedings of the 37th Annual Meeting of the Cognitive Science Society, CogSci 2015
EditorsDavid C. Noelle, Rick Dale, Anne Warlaumont, Jeff Yoshimi, Teenie Matlock, Carolyn D. Jennings, Paul P. Maglio
PublisherThe Cognitive Science Society
Pages674-679
Number of pages6
ISBN (Electronic)9780991196722
StatePublished - 2015
Externally publishedYes
Event37th Annual Meeting of the Cognitive Science Society: Mind, Technology, and Society, CogSci 2015 - Pasadena, United States
Duration: Jul 23 2015Jul 25 2015

Publication series

NameProceedings of the 37th Annual Meeting of the Cognitive Science Society, CogSci 2015

Conference

Conference37th Annual Meeting of the Cognitive Science Society: Mind, Technology, and Society, CogSci 2015
Country/TerritoryUnited States
CityPasadena
Period7/23/157/25/15

Keywords

  • artificial language learning
  • language acquisition
  • language processing
  • language production

ASJC Scopus subject areas

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

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