MEGALEX: A megastudy of visual and auditory word recognition

  • Ludovic Ferrand
  • Alain Méot
  • Elsa Spinelli
  • Boris New
  • Christophe Pallier
  • Patrick Bonin
  • Stéphane Dufau
  • Sebastiaan Mathôt
  • Jonathan Grainger
Article

Abstract

Using the megastudy approach, we report a new database (MEGALEX) of visual and auditory lexical decision times and accuracy rates for tens of thousands of words. We collected visual lexical decision data for 28,466 French words and the same number of pseudowords, and auditory lexical decision data for 17,876 French words and the same number of pseudowords (synthesized tokens were used for the auditory modality). This constitutes the first large-scale database for auditory lexical decision, and the first database to enable a direct comparison of word recognition in different modalities. Different regression analyses were conducted to illustrate potential ways to exploit this megastudy database. First, we compared the proportions of variance accounted for by five word frequency measures. Second, we conducted item-level regression analyses to examine the relative importance of the lexical variables influencing performance in the different modalities (visual and auditory). Finally, we compared the similarities and differences between the two modalities. All data are freely available on our website (https://sedufau.shinyapps.io/megalex/) and are searchable at www.lexique.org, inside the Open Lexique search engine.

Keywords

Megastudy Word recognition Lexical decision Visual Auditory modalities 

Supplementary material

13428_2017_943_MOESM1_ESM.doc (27 kb)
ESM 1(DOC 27 kb)

References

  1. Adelman, J. S., Marquis, S. J., Sabatos-DeVito, M. G., & Estes, Z. (2013). The unexplained nature of reading. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 1037–1053. doi:10.1037/a0031829 PubMedGoogle Scholar
  2. Baayen, R. H., Feldman, L. F., & Schreuder, R. (2006). Morphological influences on the recognition of monosyllabic monomorphemic words. Journal of Memory and Language, 55, 290–313. doi:10.1016/j.jml.2006.03.008 CrossRefGoogle Scholar
  3. Baayen, R. H., Piepenbrock, R., & Gulikers, L. (1995). The CELEX lexical database (Release 2, CD-ROM). Philadelphia: Linguistic Data Consortium, University of Pennsylvania.Google Scholar
  4. Balota, D. A., Cortese, M. J., Sergent-Marshall, S. D., Spieler, D. H., & Yap, M. J. (2004). Visual word recognition for single syllable words. Journal of Experimental Psychology: General, 133, 283–316. doi:10.1037/0096-3445.133.2.283 CrossRefGoogle Scholar
  5. Balota, D. A., Yap, M. J., Cortese, M. J., Hutchison, K. I., Kessler, B., Loftis, B., … & Treiman, R. (2007). The English Lexicon Project. Behavior Research Methods, 39, 445–459. doi:10.3758/BF03193014
  6. Balota, D. A., Yap, M. J., Hutchison, K. A., & Cortese, M. J. (2012). Megastudies: What do millions (or so) of trials tell us about lexical processing? In J. S. Adelman (Ed.), Visual word recognition (Models and methods, orthography and phonology, Vol. 1, pp. 90–115). Hove: Psychology Press.Google Scholar
  7. Bonin, P., Barry, C., Méot, A., & Chalard, M. (2004). The influence of age of acquisition in word reading and other tasks: A never ending story? Journal of Memory and Language, 50, 456–476. doi:10.1016/j.jml.2004.02.001 CrossRefGoogle Scholar
  8. Bonin, P., Méot, A., Ferrand, L., & Bugaïska, A. (2015). Sensory experience ratings (SERs) for 1,659 French words: Relationships with other psycholinguistic variables and visual word recognition. Behavior Research Methods, 47, 813–825.CrossRefPubMedGoogle Scholar
  9. Brysbaert, M., & New, B. (2009). Moving beyond Kucera and Francis: A critical evaluation of present word frequency norms and the introduction of a new and improved word frequency measure for American English. Behavior Research Methods, 41, 977–990. doi:10.3758/BRM.41.4.977 CrossRefPubMedGoogle Scholar
  10. Brysbaert, M., Stevens, M., Mandera, P., & Keuleers, E. (2016). The impact of word prevalence on lexical decision times: Evidence from the Dutch Lexicon Project 2. Journal of Experimental Psychology: Human Perception and Performance, 42, 441–458. doi:10.1037/xhp0000159 PubMedGoogle Scholar
  11. Brysbaert, M., Warriner, A. B., & Kuperman, V. (2014). Concreteness ratings for 40 thousand generally known English word lemmas. Behavior Research Methods, 46, 904–911. doi:10.3758/s13428-013-0403-5 CrossRefPubMedGoogle Scholar
  12. Cleland, A. A., Gaskell, M. G., Quinlan, P. T., & Tamminen, J. (2006). Frequency effects in spoken and visual word recognition: Evidence from dual-task methodologies. Journal of Experimental Psychology: Human Perception and Performance, 32, 104–119.PubMedGoogle Scholar
  13. Cleveland, W. S. (1981). LOWESS: A program for smoothing scatterplots by robust locally weighted regression. American Statistician, 35, 54.CrossRefGoogle Scholar
  14. Connine, C. M., Mullennix, J., Shernoff, E., & Yellen, J. (1990). Word familiarity and frequency in visual and auditory word recognition. Journal of Experimental Psychology: Learning, Memory, and Cognition, 16, 1084–1096. doi:10.1037/0278-7393.16.6.1084 PubMedGoogle Scholar
  15. Cortese, M. J., & Khanna, M. M. (2007). Age of acquisition predicts naming and lexical-decision performance above and beyond 22 other predictor variables: An analysis of 2,342 words. Quarterly Journal of Experimental Psychology, 60, 1072–1082. doi:10.1080/17470210701315467 CrossRefGoogle Scholar
  16. Dufau, S., Duñabeita, J. A., Moret-Tatay, C., McGonigal, A., Peeters, D., Alario, F. X., … & Grainger, J. (2011). Smart phone, smart science: How the use of smartphones can revolutionize research in cognitive science. PLoS ONE, 6, e24974. doi:10.1371/journal.pone.0024974
  17. Dufau, S., Grainger, J., Midgley, K. J., & Holcomb, P. J. (2015). A thousand words are worth a picture: Snapshots of printed-word processing in an event-related potential megastudy. Psychological Science, 26, 1887–1897.CrossRefPubMedPubMedCentralGoogle Scholar
  18. Dufau, S., Grainger, J., & Ziegler, J. C. (2012). How to say “no” to a nonword: A leaky competing accumulator model of lexical decision. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38, 1117–1128.PubMedGoogle Scholar
  19. Ernestus, M., & Cutler, A. (2015). BALDEY: A database of auditory lexical decisions. Quarterly Journal of Experimental Psychology, 68, 1469–1488. doi:10.1080/17470218.2014.984730 CrossRefGoogle Scholar
  20. Faust, M. E., Balota, D. A., Spieler, D. H., & Ferraro, F. R. (1999). Individual differences in information-processing rate and amount: Implications for group differences in response latency. Psychological Bulletin, 125, 777–799. doi:10.1037/0033-2909.125.6.777 CrossRefPubMedGoogle Scholar
  21. Ferrand, L., Bonin, P., Méot, A., Augustinova, M., New, B., Pallier, C., & Brysbaert, M. (2008). Age-of-acquisition and subjective frequency estimates for all generally known monosyllabic French words and their relation with other psycholinguistic variables. Behavior Research Methods, 40, 1049–1054. doi:10.3758/BRM.40.4.1049 CrossRefPubMedGoogle Scholar
  22. Ferrand, L., Brysbaert, M., Keuleers, E., New, B., Bonin, P., Méot, A., … & Pallier, C. (2011). Comparing word processing times in naming, lexical decision, and progressive demasking: Evidence from Chronolex. Frontiers in Psychology, 2, 306. doi:10.3389/fpsyg.2011.00306
  23. Ferrand, L., Méot, A., Spinelli, E., New, B., Pallier, C., Bonin, P., … & Grainger, J. (2015, September). MEGALEX: A new mega-study of visual word recognition. Some preliminary data. Article presented at the 19th Meeting of the European Society for Cognitive Psychology, Paphos, Cyprus.Google Scholar
  24. Ferrand, L., New, B., Brysbaert, M., Keuleers, E., Bonin, P., Méot, A., … & Pallier, C. (2010). The French Lexicon Project: Lexical decision data for 38,840 French words and 38,840 pseudowords. Behavior Research Methods, 42, 488–496. doi:10.3758/BRM.42.2.488
  25. Forster, K. I. (2000). The potential for experimenter bias effects in word recognition experiments. Memory & Cognition, 28, 1109–1115. doi:10.3758/BF03211812 CrossRefGoogle Scholar
  26. Gimenes, M., Brysbaert, M., & New, B. (2016). The processing of singular and plural nouns in English, French, and Dutch: New insights from megastudies. Canadian Journal of Experimental Psychology, 70, 316–324.CrossRefPubMedGoogle Scholar
  27. Gimenes, M., & New, B. (2016). Worldlex: Twitter and blog word frequencies for 66 languages. Behavior Research Methods, 48, 963–972.CrossRefPubMedGoogle Scholar
  28. Goh, W. D., Suárez, L., Yap, M. J., & Tan, S. H. (2009). Distributional analyses in auditory lexical decision: Neighborhood density and word-frequency effects. Psychonomic Bulletin & Review, 16, 882–887. doi:10.3758/PBR.16.5.882 CrossRefGoogle Scholar
  29. Goh, W. D., Yap, M. J., Lau, M. C., Ng, M. M. R., & Tan, L.-C. (2016). Semantic richness effects in spoken word recognition: A lexical decision and semantic categorization megastudy. Frontiers in Psychology, 7, 976. doi:10.3389/fpsyg.2016.00976 CrossRefPubMedPubMedCentralGoogle Scholar
  30. Goldinger, S. D. (1996). Auditory lexical decision. Language and Cognitive Processes, 11, 559–567.CrossRefGoogle Scholar
  31. Goldinger, S. D., Luce, P. A., & Pisoni, D. B. (1989). Priming lexical neighbors of spoken words: Effects of competition and inhibition. Journal of Memory and Language, 28, 501–518.CrossRefPubMedPubMedCentralGoogle Scholar
  32. Goodman, J. C., & Huttenlocher, J. (1988). Do we know how people identify spoken words? Journal of Memory and Language, 27, 684–698.CrossRefGoogle Scholar
  33. Grainger, J. (2017). Orthographic processing: A “mid-level” vision of reading. Quarterly Journal of Experimental Psychology. doi:10.1080/17470218.2017.1314515 Google Scholar
  34. Grainger, J., & Jacobs, A. M. (1996). Orthographic processing in visual word recognition: A multiple read-out model. Psychological Review, 103, 518–565. doi:10.1037/0033-295X.103.3.518 CrossRefPubMedGoogle Scholar
  35. Izura, C., Wright, V. C., & Fouquet, N. (2014). Hemispheric asymmetries in word recognition as revealed by the orthographic uniqueness point effect. Frontiers in Psychology, 5, 244. doi:10.3389/fpsyg.2014.00244 CrossRefPubMedPubMedCentralGoogle Scholar
  36. Juhasz, B. J., & Yap, M. J. (2013). Sensory experience ratings for over 5,000 mono- and disyllabic words. Behavior Research Methods, 45, 160–168. doi:10.3758/s13428-012-0242-9 CrossRefPubMedGoogle Scholar
  37. Juhasz, B., Yap, M. J., Dicke, J., Taylor, S. C., & Gullick, M. M. (2011). Tangible words are recognized faster: The grounding of meaning in sensory and perceptual systems. Quarterly Journal of Experimental Psychology, 64, 1683–1691. doi:10.1080/17470218.2011.605150 CrossRefGoogle Scholar
  38. Keuleers, E., & Balota, D. (2015). Megastudies, crowdsourcing, and large datasets in psycholinguistics: An overview of recent developments. Quarterly Journal of Experimental Psychology, 68, 1457–1468.CrossRefGoogle Scholar
  39. Keuleers, E., Brysbaert, M., & New, B. (2010). SUBTLEX-NL: A new frequency measure for Dutch words based on film subtitles. Behavior Research Methods, 42, 643–650. doi:10.3758/BRM.42.3.643 CrossRefPubMedGoogle Scholar
  40. Keuleers, E., Diependaele, K., & Brysbaert, M. (2010). Practice effects in large-scale visual word recognition studies: A lexical decision study on 14,000 Dutch mono- and disyllabic words and nonwords. Frontiers in Language Sciences, 1, 174. doi:10.3389/fpsyg.2010.00174 Google Scholar
  41. Keuleers, E., Lacey, P., Rastle, K., & Brysbaert, M. (2012). The British Lexicon Project: Lexical decision data for 28,730 monosyllabic and disyllabic English words. Behavior Research Methods, 44, 287–304. doi:10.3758/s13428-011-0118-4 CrossRefPubMedGoogle Scholar
  42. Keuleers, E., Stevens, M., Mandera, P., & Brysbaert, M. (2015). Word knowledge in the crowd: Measuring vocabulary size and word prevalence in a massive online experiment. Quarterly Journal of Experimental Psychology, 68, 1665–1692.CrossRefGoogle Scholar
  43. Kuperman, V., Estes, Z., Brysbaert, M., & Warriner, A. B. (2014). Emotion and language: Valence and arousal affect word recognition. Journal of Experimental Psychology: General, 143, 1065–1081. doi:10.1037/a0035669 CrossRefGoogle Scholar
  44. Kuperman, V., Stadthagen-Gonzalez, H., & Brysbaert, M. (2012). Age-of-acquisition ratings for 30 thousand English words. Behavior Research Methods, 44, 978–990. doi:10.3758/s13428-012-0210-4 CrossRefPubMedGoogle Scholar
  45. Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2013). lmerTest: Tests in linear mixed effect models. Retrieved from https:/cran.r-project.org/web/packages/lmerTest/
  46. Kwantes, P. J., & Mewhort, D. J. K. (1999). Evidence for sequential processing in visual word recognition. Journal of Experimental Psychology: Human Perception and Performance, 25, 376–381. doi:10.1037/0096-1523.25.2.376 Google Scholar
  47. Lamberts, K. (2005). Interpretation of orthographic uniqueness point effects in visual word recognition. Journal of Experimental Psychology: Human Perception and Performance, 31, 14–19.PubMedGoogle Scholar
  48. Lindell, A. K., Nicholls, M. E. R., & Castles, A. E. (2003). The effect of orthographic uniqueness and deviation points on lexical decisions: Evidence from unilateral and bilateral-redundant presentations. Quarterly Journal of Experimental Psychology, 56, 287–307.CrossRefPubMedGoogle Scholar
  49. Luce, P. A., & Pisoni, D. B. (1998). Recognizing spoken words: The neighborhood activation model. Ear and Hearing, 19, 1–36.CrossRefPubMedPubMedCentralGoogle Scholar
  50. Marlsen-Wilson, W. D. (1990). Activation, competition, and frequency in lexical access. In G. T. M. Altmann (Ed.), Cognitive models of speech processing (pp. 148–172). Cambridge: MIT Press.Google Scholar
  51. Mathôt, S., Schreij, D., & Theeuwes, J. (2012). OpenSesame: An open-source, graphical experiment builder for the social sciences. Behavior Research Methods, 44, 314–324. doi:10.3758/s13428-011-0168-7 CrossRefPubMedGoogle Scholar
  52. Miller, B., Juhasz, B. J., & Rayner, K. (2006). The orthographic uniqueness point and eye movements during reading. British Journal of Psychology, 97, 191–216.CrossRefPubMedGoogle Scholar
  53. New, B., Brysbaert, M., Véronis, J., & Pallier, C. (2007). The use of film subtitles to estimate word frequencies. Applied Psycholinguistics, 28, 661–677. doi:10.1017/S014271640707035X CrossRefGoogle Scholar
  54. New, B., Ferrand, L., Pallier, C., & Brysbaert, M. (2006). Reexamining the word length effect in visual word recognition: New evidence from the English Lexicon Project. Psychonomic Bulletin & Review, 13, 45–52. doi:10.3758/BF03193811 CrossRefGoogle Scholar
  55. New, B., Pallier, C., Brysbaert, M., & Ferrand, L. (2004). Lexique 2: A new French lexical database. Behavior Research Methods, Instruments, & Computers, 36, 516–524. doi:10.3758/BF03195598 CrossRefGoogle Scholar
  56. New, B., Pallier, C., Ferrand, L., & Matos, R. (2001). Une base de données lexicales du français contemporain sur internet: LEXIQUE. L’Année Psychologique, 101, 447–462. doi:10.3406/psy.2001.1341 CrossRefGoogle Scholar
  57. Petrova, A., Gaskell, G., & Ferrand, L. (2011). Orthographic consistency and word-frequency effects in auditory word recognition: New evidence from lexical decision and rime detection. Frontiers in Psychology, 2, 263. doi:10.3389/fpsyg.2011.00263 CrossRefPubMedPubMedCentralGoogle Scholar
  58. R Development Core Team. (2016). R: A language and environment for statistical computing. Vienna. Retrieved from www.r-project.org
  59. Radeau, M., & Morais, J. (1990). The uniqueness point effect in the shadowing of spoken words. Speech Communication, 9, 155–164. doi:10.1016/0167-6393(90)90068-K CrossRefGoogle Scholar
  60. Radeau, M., Morais, J., Mousty, P., Saerens, M., & Bertelson, P. (1992). A listener’s investigation of printed word processing. Journal of Experimental Psychology: Human Perception and Performance, 18, 861–871. doi:10.1037/0096-1523.18.3.861 Google Scholar
  61. Radeau, M., Morais, J., Mousty, P., & Bertelson, P. (2000). The effect of speaking rate on the role of the uniqueness point in spoken word recognition. Journal of Memory and Language, 42, 406–422.CrossRefGoogle Scholar
  62. Radeau, M., Mousty, P., & Bertelson, P. (1989). The effect of the uniqueness point in spoken-word recognition. Psychological Research, 51, 123–128.CrossRefPubMedGoogle Scholar
  63. Schröter, P., & Schroeder, S. (2017). The Developmental Lexicon Project: A behavioral database to investigate visual word recognition across the lifespan. Behavior Research Methods. doi:10.3758/s13428-016-0851-9 PubMedGoogle Scholar
  64. Segui, J. (1994). Language perception in visual and auditory modalities: Similarities and differences. In P. Eelen, G. d’Ydewalle, & P. Bertelson (Eds.), International perspectives on psychological science: II. The state of the art (pp. 119–134). Hove: Psychology Press.Google Scholar
  65. Seidenberg, M. S., & Waters, G. S. (1989). Word recognition and naming: A mega study. Bulletin of the Psychonomic Society, 27, 489.Google Scholar
  66. Shimizu, H. (2002). Measuring keyboard response delays by comparing keyboard and joystick inputs. Behavior Research Methods, Instruments, & Computers, 34, 250–256.CrossRefGoogle Scholar
  67. Spieler, D. H., & Balota, D. A. (1997). Bringing computational models of word naming down to the item level. Psychological Science, 8, 411–416. doi:10.1111/j.1467-9280.1997.tb00453.x CrossRefGoogle Scholar
  68. Suárez, L., Tan, S. H., Yap, M. J., & Goh, W. D. (2011). Observing neighborhood effects without neighbors. Psychonomic Bulletin & Review, 18, 605–611. doi:10.3758/s13423-011-0078-9 CrossRefGoogle Scholar
  69. Taft, M., & Hambly, G. (1986). Exploring the cohort model of spoken word recognition. Cognition, 22, 259–282.CrossRefPubMedGoogle Scholar
  70. Treiman, R., Mullennix, J., Bijeljac-Babic, R., & Richmond-Welty, E. D. (1995). The special role of rimes in the description, use, and acquisition of English orthography. Journal of Experimental Psychology: General, 124, 107–136.CrossRefGoogle Scholar
  71. Tse, C.-S., Yap, M. J., Chan, Y.-L., Sze, W. P., Shaoul, C., & Lin, D. (2016). The Chinese Lexicon Project: A megastudy of lexical decision performance for 25,000+ traditional Chinese two-character compound words. Behavior Research Methods. doi:10.3758/s13428-016-0810-5 Google Scholar
  72. Vitevitch, M. S., & Luce, P. A. (1999). Probablistic phonotactics and neighborhood activation in spoken word recognition. Journal of Memory and Language, 40, 374–408.CrossRefGoogle Scholar
  73. Yap, M. J., & Balota, D. A. (2009). Visual word recognition of multisyllabic words. Journal of Memory and Language, 60, 502–529. doi:10.1016/j.jml.2009.02.001 CrossRefGoogle Scholar
  74. Yap, M. J., & Brysbaert, M. (2009). Auditory lexical decision: On the relative weights of word frequency, neighborhood density, word length, and onset duration. Unpublished manuscript retrieved at crr.ugent.be/members/marc-brysbaert#pu6
  75. Yap, M. J., Pexman, P. M., Wellsby, M., Hargreaves, J. S., & Huff, M. (2012). An abundance of riches: Cross-task comparisons of semantic richness effects in visual word recognition. Frontiers in Human Neuroscience, 6, 72. doi:10.3389/fnhum.2012.00072 CrossRefPubMedPubMedCentralGoogle Scholar
  76. Yap, M. J., Rickard Liow, S. J., Jalil, S. B., & Faizal, S. S. B. (2010). The Malay Lexicon Project: A database of lexical statistics for 9,592 words. Behavior Research Methods, 42, 992–1003. doi:10.3758/BRM.42.4.992 CrossRefPubMedGoogle Scholar
  77. Yarkoni, T., Balota, D. A., & Yap, M. (2008). Moving beyond Coltheart’s N: A new measure of orthographic similarity. Psychonomic Bulletin & Review, 15, 971–979. doi:10.3758/PBR.15.5.971 CrossRefGoogle Scholar
  78. Ziegler, J. C., Muneaux, M., & Grainger, J. (2003). Neighborhood effects in auditory word recognition: Phonological competition and orthographic facilitation. Journal of Memory and Language, 48, 779–793.CrossRefGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2017

Authors and Affiliations

  • Ludovic Ferrand
    • 1
  • Alain Méot
    • 1
  • Elsa Spinelli
    • 2
  • Boris New
    • 3
  • Christophe Pallier
    • 4
  • Patrick Bonin
    • 5
  • Stéphane Dufau
    • 6
  • Sebastiaan Mathôt
    • 6
    • 7
  • Jonathan Grainger
    • 6
  1. 1.Université Clermont Auvergne, CNRS, Laboratoire de Psychologie Sociale et Cognitive (LAPSCO, UMR 6024)Clermont-FerrandFrance
  2. 2.CNRS and Université Pierre Mendès-France GrenobleFrance
  3. 3.CNRS and Université Savoie Mont BlancChambéryFrance
  4. 4.Gif-sur-YvetteFrance
  5. 5.CNRS and Université de Bourgogne Franche-ComtéDijonFrance
  6. 6.Laboratoire de Psychologie Cognitive (UMR 7290), Brain and Language Research InstituteMarseilleFrance
  7. 7.Department of Experimental PsychologyUniversity of GroningenNetherlands

Personalised recommendations