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The role of semantic transparency in visual word recognition of compound words: A megastudy approach

  • Say Young KimEmail author
  • Melvin J. Yap
  • Winston D. Goh
Article

Abstract

Previous studies on visual word recognition of compound words have provided evidence for the influence of lexical properties (e.g., length, frequency) and semantic transparency (the degree of relatedness in meaning between a compound word and its constituents) in morphological processing (e.g., to what extent is doorbell influenced by door and bell?). However, a number of questions in this domain, which are difficult to address with the available methodological resources, are still unresolved. We collected semantic transparency scores for 2,861 compound words at the constituent level (i.e., how strongly the overall meaning of a compound word is related to that of each constituent) and analyzed their effects on speeded pronunciation and lexical decision performance for the compound words using the English Lexicon Project (http://elexicon.wustl.edu) data. The results from both tasks indicated that our human-judged semantic transparency ratings for both the first and second constituents play a significant role in compound word processing. Moreover, additional analyses indicated that the human-judged semantic transparency scores at the constituent level accounted for more variance in compound word recognition performance than did either whole-word semantic transparency scores or corpus-based semantic distance scores.

Keywords

Visual word recognition Compound word Megastudy Semantic transparency 

Notes

Supplementary material

13428_2018_1143_MOESM1_ESM.csv (197 kb)
ESM 1 (CSV 197 kb)

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Copyright information

© Psychonomic Society, Inc. 2018

Authors and Affiliations

  • Say Young Kim
    • 1
    • 2
    Email author
  • Melvin J. Yap
    • 1
  • Winston D. Goh
    • 1
  1. 1.Department of PsychologyNational University of SingaporeSingaporeSingapore
  2. 2.Department of English Language and LiteratureHanyang UniversitySeoulSouth Korea

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