Competition between multiple words for a referent in cross-situational word learning

Viridiana Benitez, Daniel Yurovsky, Linda B. Smith

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

Three experiments investigated competition between word-object pairings in a cross-situational word-learning paradigm. Adults were presented with One-Word pairings, where a single word labeled a single object, and Two-Word pairings, where two words labeled a single object. In addition to measuring learning of these two pairing types, we measured competition between words that refer to the same object. When the word-object co-occurrences were presented intermixed in training (Experiment 1), we found evidence for direct competition between words that label the same referent. Separating the two words for an object in time eliminated any evidence for this competition (Experiment 2). Experiment 3 demonstrated that adding a linguistic cue to the second label for a referent led to different competition effects between adults who self-reported different language learning histories, suggesting both distinctiveness and language learning history affect competition. Finally, in all experiments, competition effects were unrelated to participants' explicit judgments of learning, suggesting that competition reflects the operating characteristics of implicit learning processes. Together, these results demonstrate that the role of competition between overlapping associations in statistical word-referent learning depends on time, the distinctiveness of word-object pairings, and language learning history.

Original languageEnglish (US)
Pages (from-to)31-48
Number of pages18
JournalJournal of Memory and Language
Volume90
DOIs
StatePublished - Oct 1 2016
Externally publishedYes

Keywords

  • Competition
  • Statistical learning
  • Word learning

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Language and Linguistics
  • Experimental and Cognitive Psychology
  • Linguistics and Language
  • Artificial Intelligence

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