Publications

Freggens, M, Thomas, A., & Pitt, M. A. (2019). A test of linguistic influences in the perceptual organization of speech.AAttention, Perception, & Psychophysics, 81,1065-1075. doi:10.3758/s13414-019-01699-3

Pitt, M. A. & Myung, J. I. (2019). Robust Modeling Through Design Optimization.Computational Brain & Behavior doi: 10.1007/s42113-019-00050-1

Shatzer, H.E., Shen, S., Kerlin, J.R., Pitt, M.A., & Shahin, A.J. (2018). Neurophysiology underlying influence of stimulus reliability on audiovisual integration.European Journal of Neuroscience,48(8), 2836-2848. doi: 10.1111/ejn.13843

Walsh, M. M., Gluck, K. A., Gunzelmann, G., Jastrzembski, T., Krusmark, M., Myung, J. I., Pitt, M.A., & Zhou, R. (2018). Mechanisms underlying the spacing effect in learning: A comparison of three computational models.Journal of Experimental Psychology: General,146(2),227-249. doi: 10.1037/xge0000416

Aranovich, G. J., Cavagnaro, D., Pitt, M. A., Myung, J. I., Matthews, C. A. (2017). A model-based analysis of decision making under risk in obsessive-compulsive and hoarding disorders.Journal of Psychiatric Research, 90, 126-132. 10.1016/j.jpsychires.2017.02.017

Armstrong, B.C., Dumay, N., Kim, W., & Pitt, M.A. (2017). Generalization from newly learned words reveals structural properties of the human reading system. Journal of Experimental Psychology: General. 146(2), 227-249. DOI:10.1037/xge0000257

Baese-Berk, M, Dilley, L.C., Schmidt, S., Morrill, T.H., & Pitt, M. A. (2016). Revisiting Neil Armstrongs Moon-Landing Quote: Implications for Speech Perception, Function Word Reduction, and Acoustic Ambiguity. PLOS ONE, 11. 10.1371/journal.pone.0155975

Cavagnaro, D. R., Aranovich, G. J., McClure, S. M., Pitt, M. A., & Myung, J. I. (2016). On the functional form of temporal discounting: An optimized adaptive test.Journal of Risk and Uncertainty, 52, 233-254.

Gu, H., Kim, W., Hou, F., Lesmes, L., Pitt, M. A., Lu, Z.-L., & Myung, J. I. (2016). A hierarchical Bayesian approach to adaptive vision testing: A case study with the contrast sensitivity function. Journal of Vision, 16(6), 1-17.

Hou, F., Lesmes, L., Kim, W., Gu, H., Pitt, M. A., Myung, J. I., & Lu, Z.-L. (2016). Evaluating the performance of the quick CSF method in detecting contrast sensitivity function changes. Journal of Vision, 16(6), 18-29

Kim, W., Pitt, M. A., Lu, Z.-L., & Myung, J. I. (2016). Planning beyond the next trial in adaptive experiments: A dynamic programming approach. Cognitive Science. DOI:10.1111/cogs.12467

Myung, J.I., Cavagnaro, D.R., & Pitt, M.A. (2016). Model evaluation and selection. In W.H. Batchelder et al (Eds.) New Handbook of Mathematical Psychology: Vol 1: Foundations and Methodology,(pp. 552-598). Cambridge, Cambridge

Pitt, M.A., Szostak, C., & Dilley, L. (2016). Rate-dependent speech processing can be speech-specific: Evidence from the perceptual disappearance of words under changes in context speech rate. Attention, Perception & Psychophysics. This file contains the additional data mentioned in Footnote 1.

Bhat, J., Miller, L. M., Pitt, M. A., & Shahin, A. J. (2015). Putative mechanisms mediating tolerance for audiovisual stimulus onset asynchrony. Journal of Neurophysiology, jn.00200.2014. doi:10.1152/jn.00200.2014

Baese-Berk, M., Heffner, C.C., Dilley, L.C., Pitt, M.A., Morrill, T.H., & McAuley, J.D. (2014). Long-term temporal tracking of speech rate affects spoken-word recognition. Psychological Science, 25, 1546-1553.

Bhat, J., Pitt, M. A., & Shahin, A. (2014). Visual context due to speech-reading suppresses the auditory response to acoustic interruptions in speech. Frontiers in Neuroscience, 8, 173. doi:10.3389/fnins.2014.00173

Kim, W., Pitt, M. A., Lu, Z.-L., Steyvers, M., & Myung, J. I. (2014). A hierarchical adaptive approach to optimal experimental design. Neural Computation, 26, 2465-2492.

Montenegro, M., Myung, J. I., & Pitt, M. A. (2014). Analytic expressoins for the REM model of recognition memory. Journal of Mathematical Psychology, 60, 23-28. doi:10.1016/j.jmp.2014.05.003

Morrill, T. H., Dilley, L. C., McAuley, J. D., & Pitt, M. A. (2014). Distal rhythm influences whether or not listeners hear a word in continuous speech: Support for a perceptual grouping hypothesis. Cognition, 131, 69-74. doi:10.1016/j.cognition.2013.12.006

Szostak, C., & Pitt, M.A. (2014). The influence of amplitude envelope information on resolving lexically ambiguous words.JASA Express Letters, 136, 249-255. doi:dx.doi.org/10.1121/1.4893331

Cavagnaro, D. R., Pitt, M. A., Gonzalez, R., & Myung, J. I. (2013). Discriminating Among Probability Weighting Functions Using Adaptive Design Optimization. Journal of Risk and Uncertainty, 47, 255-289. doi:10.1007/s11166-013-9179-3

Cavagnaro, D. R., Gonzalez, R., Myung, J. I., & Pitt, M. A. (2013). Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach. Management Science, 59, 358-375. doi:10.1287/mnsc.1120.1558

Heffner, C. C., Dilley, L. C., McAuley, J. D., & Pitt, M. A. (2013). When cues combine: How distal and proximal acoustic cues are integrated in word segmentation. Language and Cognitive Processes, 28, 1275-1302. doi:10.1080/01690965.2012.672229

Kim, W., Pitt, M. A., & Myung, J. I. (2013). How do PDP models learn quasiregularity? Psychological Review, 120, 903-916. doi:10.1037/a0034195.

Myung, J. I., Cavagnaro, D. R.,& Pitt, M. A. (2013). A tutorial on adaptive design optimization. Journal of Mathematical Psychology, 57, 53-67. doi:10.1016/j.jmp.2013.05.005

Pitt, M.A., & Tang, Y. (2013). What should be the data sharing policy of cognitive science. Topics in Cognitive Science, 5, 214-221.

Szostak, C., & Pitt, M.A., (2013). The Prolonged Influence of Subsequent Context on Spoken Word Recognition, Attention, Perception & Psychophysics, 27, 1225-1239. doi:10.3758/s13414-013-0492-3

Shahin, A.J., & Pitt, M.A. (2012). Alpha activity marking word boundaries mediates speech segmentation. European Journal of Neuroscience, 36(12), 3740-3748. doi:10.1111/ejn.12008

Kim, D., Stephens, J. D. W., & Pitt, M. A. (2012). How does context play a part in splitting words apart? Production and perception of word boundaries in casual speech. Journal of Memory and Language, 66(4), 509-529.

Pitt, M. A., & Szostak, C. M. (2012). A lexically biased attentional set compensates for variable speech quality caused by pronunciation variation. Language and Cognitive Processes, 27, 1225-1239. doi:10.1080/01690965.2011.619370

Cavanaro, D.R., Pitt, M.A., & Myung, J.I. (2011). Model Discrimination through Adaptive Experimentation. Psychonomic Bulletin & Review, 18, 204-210.

Pitt, M.A., Dilley, L., & Tat, M. (2011). Exploring the role of exposure frequency in recognizing pronunciation variants. Journal of Phonetics, 39, 304-311. This file contains the additional data mentioned in footnote 4.

Dilley, L., & Pitt, M.A. (2010).Altering context speech rate can cause words to appear and disappear. Psychological Science, 21, 1664-1670.

Myung, J.I., Tang, Y., & Pitt, M.A. (2010). Evaluation and Comparison of Computational Models. In M.L. Johnson (Ed.), Essential Numerical Computer Methods. (pp. 511-527). New York: Elsevier.

Cavanaro, D.R., Myung, J.I., Pitt, M.A. & Kujala, J.V. (2010). Adaptive Design Optimization: A Mutual Information Based Approach to Model Discrimination in Cognitive Science. Neural Computation, 22, 887-905.

Myung, J.I., & Pitt, M.A. (2009). Optimal Experimental Design for Model Discrimination. Psychological Review, 116, 499-518.

Pitt, M.A. (2009). How are pronunciation variants of spoken words recognized? A test of generalization to newly learned words. Journal of Memory and Language, 61, 19-36. This file contains the labeling and RT graphs mentioned in Footnote 5.

Pitt, M.A. (2009). The strength and time course of lexical activation of pronunciation variants. Journal of Experimental Psychology: Human Perception and Performance, 35, 896-910. This file contains the TRACE simulation mentioned in Footnote 2.

Myung, J.I., Tang, Y., & Pitt, M.A. (2009). Evaluation and Comparison of Computational Models. Methods in Enzymology, 287-304.

Pitt, M.A., Myung, J.I., Montenegro, M., & Pooley, J. (2008). Measuring the flexibility of localist connectionist models of speech perception. Cognitive Science, 32, 1285-1303.

Dilley, L., & Pitt, M.A. (2007). A study of regressive place assimilation in spontaneous speech and its implications for spoken word recognition. Journal of the Acoustical Society of America., 122, 2340-2353.

Myung, J.I., Montenegro, M., & Pitt, M.A. (2007). Analytic expressions for the BCDMEM model of recognition memory Journal of Mathematical Psychology, 51, 198-204.

Myung, J.I., Pitt, M.A., & Navarro, D.J. (2007). Does Response Scaling Cause the Generalized Context Model to Mimic a Prototype Model? Psychonomic Bulletin & Review, 14, 1043-1050.

Pitt, M.A., Dilley, L., Johnson, K., Kiesling, S., Raymond, W., Hume, E. and Fosler-Lussier, E. (2007) Buckeye Corpus of Conversational Speech (2007; Final release) [www.buckeyecorpus.osu.edu] Columbus, OH: Department of Psychology, Ohio State University (Distributor).

Pitt, M.A., Myung, J.I., & Altieri, N. (2007). Modeling the word recognition data of Vitevitch and Luce (1998): Is it ARTful? Psychonomic Bulletin & Review, 14, 442-448.

Myung, J. I., Navarro, D. J. & Pitt, M. A. (2006). Model selection by normalized maximum likelihood. Journal of Mathematical Psychology, 50, 167-179.

Pitt, M.A., Kim, W., Navarro, D.J., & Myung, J.I. (2006). Global model analysis by parameter space partitioning. Psychological Review, 113, 57-83.

Pitt, M.A., & Samuel, A.G. (2006). Word Length and Lexical Activation: Longer is Better. Journal of Experimental Psychology: Human Perception and Performance, 32, 1120-1135. This file contains a description of the replication of Experiment 3 mentioned in Footnote 6.

Grunwald, P., Myung, I., & Pitt, M.A. (2005). Advances in Minimum Description Length: Theory and Application. Cambridge, MA: MIT Press.

Pitt, M.A., Johnson, K., Hume, E., Kiesling, S., & Raymond W. (2005). The Buckeye Corpus of Conversational Speech: Labeling Conventions and a Test of Transcriber Reliability. Speech Communication, 45, 89-95.

Navarro, D., Pitt, M.A., & Myung, I. (2004). Assessing the Distinguishability of Models and the Informativeness of Data. Cognitive Psychology, 49, 47-84.

Pitt, M.A., Kim, W., & Myung, I.J. (2003). Flexibility versus Generalizability in Model Selection. Psychonomic Bulletin & Review, 10, 29-44.

Samuel, A.G., & Pitt, M.A. (2003). Lexical activation (and other factors) can mediate compensation for coarticulation. Journal of Memory and Language, 48, 416-434.

Pitt, M.A., & Myung, I.J. (2002). When a good fit can be bad. Trends in Cognitive Science, 6, 421-425. TICS homepage

Pitt, M.A. & Shoaf, L.S. (2002). Revisiting bias effects in word-initial phonological priming.Journal of Experimental Psychology: Human Perception and Performance, 28, 1120-1130. Figures mentioned in Footnote 3.

Shoaf, L.S., & Pitt, M.A. (2002). Does node stability underlie the Verbal Transformation Effect? A Test of Node Structure Theory. Perception & Psychophysics, 64, 795-803.

Pitt, M.A., Myung, I., & Zhang, S. (2002). Toward a method of selecting among computational models of cognition. Psychological Review, 109, 472-491.

Pitt, M.A., & Shoaf, L. (2002). Linking verbal transformations to their causes. Journal of Experimental Psychology: Human Perception and Performance, 28, 150-162. Additional figures. Stim

Pitt, M.A., & Shoaf, L. (2001). The source of a lexical bias in the Verbal Transformation Effect. Language and Cognitive Processes, 16, 5/6, 715-721.

Pitt, M.A. (1998). Phonological processes and the perception of phonotactically illegal consonant clusters. Perception & Psychophysics, 60, 941-951. Figure mentioned in footnote 2 in Experiment 2.