How orthographic-specific characteristics shape letter position coding: The case of Thai script

Brief Report

Abstract

A central question for any model of visual word identification is the representation of the position at which letters are encoded (e.g., calm vs. clam). In this article, we examine whether the orthographic-specific characteristics of a writing system—namely, Thai—shape the process of letter position coding. Thai is an alphabetic script that lacks interword spaces and has an orthographic order that does not necessarily correspond to the phonological order for initial vowels. This implies that the initial letter position coding in Thai needs to be flexible enough that readers can successfully encode the letter positions of words. To compare letter position coding in Thai to that in English, we conducted an experiment that paralleled Experiment 3 in Gomez, Ratcliff, and Perea (Psychological Review, 115, 577–600, 2008), including 23 conditions (single-letter replacements, letter transpositions, letter migrations, and a corresponding control). We obtained fits from Gomez et al.’s overlap model, which is a model that has been shown to account for letter position coding in the Roman alphabet across this variety of letter manipulations. The overlap model was found to successfully fit the Thai data. Our results revealed that the position encoding was better for the first letter than for the rest of the positions in both languages; however, in English the position uncertainty grows as a function of letter order quite abruptly, whereas in Thai it grows gradually. Thus, the orthographic-specific characteristics of the Thai writing system do play a role in shaping the process of letter position coding.

Keywords

Visual word recognition Modeling Letter position coding 

References

  1. Adelman, J. S. (2011). Letters in time and retinotopic space. Psychological Review, 118, 570–582. doi:10.1037/a0024811 CrossRefPubMedGoogle Scholar
  2. Aroonmanakun, W. (2007). Creating the Thai National Corpus. Manusaya, 13, 4–17.Google Scholar
  3. Davis, C. J. (2010). The spatial coding model of visual word identification. Psychological Review, 117, 713–758. doi:10.1037/a0019738 CrossRefPubMedGoogle Scholar
  4. Forster, K. I., & Forster, J. C. (2003). DMDX: A Windows display program with millisecond accuracy. Behavior Research Methods, Instruments, & Computers, 35, 116–124. doi:10.3758/bf03195503 CrossRefGoogle Scholar
  5. Gomez, P., Ratcliff, R., & Perea, M. (2008). The overlap model: A model of letter position coding. Psychological Review, 115, 577–600. doi:10.1037/a0012667 CrossRefPubMedPubMedCentralGoogle Scholar
  6. Grainger, J., Granier, J. P., Farioli, F., Van Assche, E., & van Heuven, W. J. (2006). Letter position information and printed word perception: The relative-position priming constraint. Journal of Experimental Psychology: Human Perception and Performance, 32, 865–884. doi:10.1037/0096-1523.32.4.865 PubMedGoogle Scholar
  7. Jeffreys, H. (1961). Theory of probability (3rd ed.). New York, NY: Oxford University Press.Google Scholar
  8. Logan, G. D. (1996). The CODE theory of visual attention: An integration of space-based and object-based attention. Psychological Review, 103, 603–649. doi:10.1037/0033-295X.103.4.603 CrossRefPubMedGoogle Scholar
  9. Nocedal, J., & Wright, S. J. (1999). Numerical optimization. New York, NY: Springer.CrossRefGoogle Scholar
  10. Norris, D., Kinoshita, S., & van Casteren, M. (2010). A stimulus sampling theory of letter identity and order. Journal of Memory and Language, 62, 254–271. doi:10.1016/j.jml.2009.11.002 CrossRefGoogle Scholar
  11. Perea, M., Abu Mallouh, R., & Carreiras, M. (2010). The search of an input coding scheme: Transposed-letter priming in Arabic. Psychonomic Bulletin & Review, 17, 375–380. doi:10.3758/pbr.17.3.375 CrossRefGoogle Scholar
  12. Perea, M., & Carreiras, M. (2006). Do transposed-letter effects occur across lexeme boundaries? Psychonomic Bulletin and Review, 13, 418–422. doi:10.3758/bf03193863 CrossRefPubMedGoogle Scholar
  13. Perea, M., Gatt, A., Moret-Tatay, C., & Fabri, R. (2012). Are all Semitic languages immune to letter transpositions? The case of Maltese. Psychonomic Bulletin & Review, 19, 942–947. doi:10.3758/s13423-012-0273-3 CrossRefGoogle Scholar
  14. Perea, M., & Lupker, S. J. (2003). Does jugde activate COURT? Transposed-letter confusability effects in masked associative priming. Memory & Cognition, 31, 829–841. doi:10.3758/bf03196438 CrossRefGoogle Scholar
  15. Perea, M., & Lupker, S. J. (2004). Can CANISO activate CASINO? Transposed-letter similarity effects with nonadjacent letter positions. Journal of Memory and Language, 51, 231–246. doi:10.1016/j.jml.2004.05.005 CrossRefGoogle Scholar
  16. Perea, M., Marcet, A., & Gomez, P. (2016). How do Scrabble players encode letter position during reading? Psicothema, 28, 7–12. doi:10.7334/psicothema2015.167 PubMedGoogle Scholar
  17. Perea, M., Winskel, H., & Ratitamkul, T. (2012). On the flexibility of letter position coding during lexical processing: The case of Thai. Experimental Psychology, 59, 68–73. doi:10.1027/1618-3169/a000127 CrossRefGoogle Scholar
  18. Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56, 356–374. doi:10.1016/j.jmp.2012.08.001 CrossRefGoogle Scholar
  19. Tóth, D., & Csépe, V. (2016). Adaptive specialization in position encoding while learning to read. Developmental Science. doi:10.1111/desc.12426 PubMedGoogle Scholar
  20. Velan, H., & Frost, R. (2011). Words with and without internal structure: What determines the nature of orthographic and morphological processing? Cognition, 118, 141–156. doi:10.1016/j.cognition.2010.11.013 CrossRefPubMedGoogle Scholar
  21. White, S. J., Johnson, R. L., Liversedge, S. P., & Rayner, K. (2008). Eye movements when reading transposed text: The importance of word-beginning letters. Journal of Experimental Psychology: Human Perception and Performance, 34, 1261–1276. doi:10.1037/0096-1523.34.5.1261 PubMedPubMedCentralGoogle Scholar
  22. Whitney, C. (2001). How the brain encodes the order of letters in a printed word: The SERIOL model and selective literature review. Psychonomic Bulletin & Review, 8, 221–243. doi:10.3758/bf03196158 CrossRefGoogle Scholar
  23. Wiley, R. W., Wilson, C., & Rapp, B. (2016). The effects of alphabet and expertise on letter perception. Journal of Experimental Psychology: Human Perception and Performance, 42, 1186–1203. doi:10.1037/xhp0000213 PubMedGoogle Scholar
  24. Winskel, H., & Iemwanthong, K. (2010). Reading and spelling acquisition in Thai children. Reading and Writing, 23, 1021–1053. doi:10.1007/s11145-009-9194-6 CrossRefGoogle Scholar
  25. Winskel, H., Perea, M., & Ratitamkul, T. (2012). On the flexibility of letter position coding during lexical processing: Evidence from eye movements when reading Thai. Quarterly Journal of Experimental Psychology, 64, 1522–1536. doi:10.1080/17470218.2012.658409 CrossRefGoogle Scholar
  26. Yakup, M., Abliz, W., Sereno, J., & Perea, M. (2015). Extending models of visual-word recognition to semicursive scripts: Evidence from masked priming in Uyghur. Journal of Experimental Psychology: Human Perception and Performance, 41, 1553–1562. doi:10.1037/xhp0000143 PubMedGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2017

Authors and Affiliations

  1. 1.Departamento de MetodologíaUniversitat de ValènciaValenciaSpain
  2. 2.Southern Cross UniversityCoffs HarbourAustralia
  3. 3.DePaul UniversityChicagoUSA

Personalised recommendations