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  • 标题:Knowledge of Statistics or Statistical Learning? Readers Prioritize the Statistics of their Native Language Over the Learning of Local Regularities
  • 本地全文:下载
  • 作者:Jarosław R. Lelonkiewicz ; Michael T. Ullman ; Davide Crepaldi
  • 期刊名称:Journal of Cognition
  • 电子版ISSN:2514-4820
  • 出版年度:2022
  • 卷号:5
  • 期号:1
  • DOI:10.5334/joc.209
  • 语种:English
  • 出版社:Ubiquity Press Ltd.
  • 摘要:A large body of evidence suggests that people spontaneously and implicitly learn about regularities present in the visual input. Although theorized as critical for reading, this ability has been demonstrated mostly with pseudo-fonts or highly atypical artificial words. We tested whether local statistical regularities are extracted from materials that more closely resemble one’s native language. In two experiments, Italian speakers saw a set of letter strings modelled on the Italian lexicon and guessed which of these strings were words in a fictitious language and which were foils. Unknown to participants, words could be distinguished from foils based on their average bigram frequency. Surprisingly, in both experiments, we found no evidence that participants relied on this regularity. Instead, lexical decisions were guided by minimal bigram frequency, a cue rooted in participants’ native language. We discuss the implications of these findings for accounts of statistical learning and visual word processing.
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