The effects of N-gram probabilistic measures on the recognition and production of four-word sequences

Mental Lexicon

Volumn 6, Issue 2, 2011, Pages 302-324

  Tremblay, Antoine ^a   Tucker, Benjamin V ^b  

^a IWK HEALTH CENTRE   (Canada)

^b UNIVERSITY OF ALBERTA   (Canada)

Author keywords

Frequency of occurrence; Log probability of occurrence; Logit; Mixed effects regression; Multi word sequences; Mutual information; N grams; Speech processing; Speech production

Indexed keywords

EID: 80051495158     PISSN: 18711340     EISSN: 18711375     Source Type: Journal    
DOI: 10.1075/ml.6.2.04tre     Document Type: Article

References (42)

1. Allen, M. (1997). Understanding Regression Analysis. New York: Plenum Press.
2. Arnon, I., & Snider, N. (2010). More than words: Frequency effects for multi-word phrases. Journal of Memory and Language, 62, 67-82.
3. Baayen, R. H. (2008). Analyzing Linguistic Data: A Practical Introduction to Statistics using R. Cambridge, U.K.: Cambridge University Press.
4. Baayen, R. H. (2011). languageR: Data Sets and Functions with "Analyzing Linguistic Data: A Practical Introduction to Statistics". [Computer software manual]. Available from http://CRAN.R-project.org/package= languageR (R package version 1.2)
5. Baayen, R. H., Davidson, D. J., & Bates, D. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory & Language, 59, 390-412.
6. Baayen, R. H., Kuperman, V., & Bertram, R. (2010). Frequency effects in compound processing. In S. Scalise & I. Vogel (Eds.), Compounding (pp. 257-270). Amsterdam and Philadelphia: John Benjamins.
7. Baayen, R. H., Wurm, L. H., & Aycock, J. (2007). Lexical dynamics for low-frequency complex words. a regression study across tasks and modalities. The Mental Lexicon, 2, 419-463.
8. Bates, D., Maechler, M., & Bolker, B. (2011). lme4: Linear Mixed-effects Models using S4 Classes [Computer software manual]. Available from http://CRAN.R-project.org/package=lme4 (R package version 0.999375-39)
9. Bell, A., Brenier, J. M., Gregory, M., Girand, C., & Jurafsky, D. (2009). Predictability effects on durations of content and function words in conversational English. Journal of Memory & Language, 60, 92-111.
10. Belsley, D. A., Kuh, E., & Welsch, R. E. (1980). Regression Diagnostics. Identifying Influential Data and Sources of Collinearity. New York: Wiley.
11. Boersma, P., & Weenink, D. (2010). Praat: Doing Phonetics by Computer (computer program).http://www.praat.org/, Version 5.1.44.
12. Bybee, J. (2001). Phonology and Language Use. Cambridge: Cambridge University Press.
13. Bybee, J. (2006). From usage to grammar: The minds response to repetition. Language, 82, 711-733.
14. Cronbach, L. J. (1987). Statistical test for moderator variables: Flaws in analyses recently proposed. Psychological Bulletin, 102, 414-417.
15. Davies, M. (2004). BYU-BNC: The British National Corpus. Available on-line at http://corpus.byu.edu/bnc.
16. Davies, M. (2008). The Corpus of Contemporary American English (COCA): 400+ Million Words, 1990-Present. Available on-line at http://www. americancorpus.org.
17. de Vaan, L., Schreuder, R., & Baayen, R. H. (2007). Regular morphologically complex neologisms leave detectable traces in the mental lexicon. The Mental Lexicon, 2, 1-24.
18. Ellis, N. C., & Simpson-Vlach, R. (2009). Formulaic language in native speakers: Triangulating psycholinguistics, corpus linguistics, and education. Corpus Linguistics & Linguistic Theory, 5, 61-78.
19. Fletcher, W. H. (2008). Phrases in English. Available on-line at http://pie.usna.edu/index.html.
20. Frisson, S., Rayner, K., & Pickering, M. J. (2005). Effects of contextual predictability and transitional probability on eye movements during reading. Journal of Experimental Psychology: Learning, Memory, & Cognition, 31, 862-877. (Pubitemid 41677495)
21. Gelman, A., & Hill, J. (2007). Data Analysis using Regression and Multilevel/Hierarchical Models. Cambridge: Cambridge University Press.
22. Glantz, S., & Slinker, B. (1990). Primer of Applied Regression and Analysis of Variance. New York: McGraw-Hill.
23. Gregory, M. L., Raymond, W. D., Bell, A., Fosler-Lussier, E., & Jurafsky, D. (1999). The effectsof collocational strength and contextual predictability in lexical production. CLS-99, 35, 151-166.
24. Harrell, F. (2001). Regression Modeling Strategies. Berlin: Springer.
25. Jurafsky, D., Bell, A., Gregory, M., & Raymond, W. (2001). Probabilistic relations between words: Evidence from reduction in lexical production. In J. Bybee & P. Hopper (Eds.), Frequency and the Emergence of Linguistic Structure (p. 229-254). Amsterdam: Benjamins.
26. Kline, R. B. (2005). Principles and Practice of Structural Equation Modeling. Second Edition. New York and London: The Guilford Press.
27. Marslen-Wilson, W. (1995). Activation, competition, and frequency in lexical access. In G. T. Altman (Ed.), Cognitive Models of Speech Processing (pp. 148-172). Cambridge, MA: MIT Press.
28. Newman, A., Tremblay, A., Nichols, E. S., Neville, H. J., & Ullman, M. (submitted). The influence of language proficiency on lexical-semantic processing in native and late learners of English: Linear mixed effects modeling of ERP and proficiency data. Journal of Cognitive Neuroscience.
29. Pinheiro, J. C., & Bates, D. M. (2000). Mixed-effects Models in S and S-PLUS. New York: Springer.
30. Pluymaekers, M., Ernestus, M., & Baayen, R. H. (2005). Lexical frequency and acoustic reduction in spoken dutch. Phonetica, 62, 146-159.
31. R Development Core Team. (2009). R: A Language and Environment for Statistical Computing [Computer software manual]. Vienna, Austria. Available from http://www.R-project.org (ISBN 3-900051-07-0)
32. Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological Bulletin, 124, 372-422. (Pubitemid 128461792)
33. Scheibman, J., & Bybee, J. (1999). The effect of usage on degrees of constituency: The reduction of don't in English. Linguistics, 37, 575-596.
34. Taft, M. (1979). Recognition of affixed words and the word frequency effect. Memory & Cognition, 7, 263-272.
35. Taylor, T. E., & Lupker, S. J. (2001). Sequential effects in naming: A time-criterion account. Journal of Experimental Psychology-learning Memory & Cognition, 27, 117-138. (Pubitemid 33684367)
36. Tremblay, A. (2009). Processing Advantages of Lexical Bundles: Evidence from Self-paced Reading, Word ad Sentence Recall, and Free Recall with Event-Related Brain Potential Recordings. PhD dissertation, University of Alberta, Edmonton, Canada.
37. Tremblay, A. (2011). LMERConvenienceFunctions: A Suite of Functions to Back-fit Fixed Effects and Forward-fit Random Effects. [Computer software manual]. Available from http://CRAN.Rproject.org/package= LMERConvenienceFunctions (R package version 1.5)
38. Tremblay, A., & Baayen, R. H. (2010). Holistic processing of regular four-word sequences: A behavioral and ERP study of the effects of structure, frequency, and probability on immediate free recall. In D. Wood (Ed.), Perspectives on Formulaic Language: Acquisition and Communication (p. 151-173). London and New York: Continuum.
39. Venables, W. (1998). Exegeses on linear models. Available from http://www.stats.ox.ac.uk/pub/MASS3/Exegeses.pdf. (Paper presented to the S-PLUS User's Conference, Washington, DC, 8-9th October, 1998).
40. Wlotko, E. W., & Federmeier, K. D. (2007). Finding the right word: Hemispheric asymmetries in the use of sentence context information. Neuropsychologia, 45, 3001-3014. (Pubitemid 47374733)
41. Wu, H., & Zhang, J. (2006). Nonparametric Regression Methods for Longitudinal Data Analysis. Hoboken, NJ: Wiley.
42. Yap, M. J., & Balota, D. A. (2009). Visual word recognition of multisyllabic words. Journal of Memory & Language, 60, 502-529.