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  1. Efthymia C. Kapnoula, Stephanie Packard, Prahlad Gupta & Bob McMurray (2015). Immediate Lexical Integration of Novel Word Forms. Cognition 134:85-99.
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  2. Bob McMurray, Kristine A. Kovack-Lesh, Dresden Goodwin & William McEchron (2013). Infant Directed Speech and the Development of Speech Perception: Enhancing Development or an Unintended Consequence? Cognition 129 (2):362-378.
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  3. Keith S. Apfelbaum & Bob McMurray (2011). Using Variability to Guide Dimensional Weighting: Associative Mechanisms in Early Word Learning. Cognitive Science 35 (6):1105-1138.
    At 14 months, children appear to struggle to apply their fairly well-developed speech perception abilities to learning similar sounding words (e.g., bih/dih; Stager & Werker, 1997). However, variability in nonphonetic aspects of the training stimuli seems to aid word learning at this age. Extant theories of early word learning cannot account for this benefit of variability. We offer a simple explanation for this range of effects based on associative learning. Simulations suggest that if infants encode both noncontrastive information (e.g., cues (...)
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  4. Jessica S. Horst, Larissa K. Samuelson, Sarah C. Kucker & Bob McMurray (2011). What's New? Children Prefer Novelty in Referent Selection. Cognition 118 (2):234-244.
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  5. Joseph C. Toscano & Bob McMurray (2010). Cue Integration with Categories: Weighting Acoustic Cues in Speech Using Unsupervised Learning and Distributional Statistics. Cognitive Science 34 (3):434.
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  6. Bob McMurray & Edward Wasserman (2009). Variability in Languages, Variability in Learning? Behavioral and Brain Sciences 32 (5):459-460.
    In documenting the dizzying diversity of human languages, Evans & Levinson (E&L) highlight the lack of universals. This suggests the need for complex learning. Yet, just as there is no universal structure, there may be no universal learning mechanism responsible for language. Language is a behavior assembled by many processes, an assembly guided by the language being learned.
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  7. Colleen Mitchell & Bob McMurray (2009). On Leveraged Learning in Lexical Acquisition and Its Relationship to Acceleration. Cognitive Science 33 (8):1503-1523.
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  8. Bob McMurray, Joel L. Dennhardt & Andrew Struck‐Marcell (2008). Context Effects on Musical Chord Categorization: Different Forms of Top‐Down Feedback in Speech and Music? Cognitive Science 32 (5):893-920.
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  9. Colleen C. Mitchell & Bob McMurray (2008). A Stochastic Model for the Vocabulary Explosion. In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society. 1919--1926.
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  10. Bob McMurray & Richard N. Aslin (2005). Infants Are Sensitive to Within-Category Variation in Speech Perception. Cognition 95 (2):B15-B26.
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  11. Bob McMurray & David Gow (2005). It's Not How Many Dimensions You Have, It's What You Do with Them: Evidence From Speech Perception. Behavioral and Brain Sciences 28 (1):31-31.
    Contrary to Pothos, rule- and similarity-based processes cannot be distinguished by dimensionality. Rather, one must consider the goal of the processing: what the system will do with the resulting representations. Research on speech perception demonstrates that the degree to which speech categories are gradient (or similarity-based) is a function of the utility of within-category variation for further processing.
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  12. James S. Magnuson, Bob McMurray, Michael K. Tanenhaus & Richard N. Aslin (2003). Lexical Effects on Compensation for Coarticulation: A Tale of Two Systems? Cognitive Science 27 (5):801-805.
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  13. James S. Magnuson, Bob McMurray, Michael K. Tanenhaus & Richard N. Aslin (2003). Lexical Effects on Compensation for Coarticulation: The Ghost of Christmash Past. Cognitive Science 27 (2):285-298.
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  14. Bob McMurray, Michael K. Tanenhaus & Richard N. Aslin (2002). Gradient Effects of Within-Category Phonetic Variation on Lexical Access. Cognition 86 (2):B33-B42.
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  15. Michael K. Tanenhaus, James S. Magnuson, Bob McMurray & Richard N. Aslin (2000). No Compelling Evidence Against Feedback in Spoken Word Recognition. Behavioral and Brain Sciences 23 (3):348-349.
    Norris et al.'s claim that feedback is unnecessary is compromised by (1) a questionable application of Occam's razor, given strong evidence for feedback in perception; (2) an idealization of the speech recognition problem that simplifies those aspects of the input that create conditions where feedback is useful; (3) Norris et al.'s use of decision nodes that incorporate feedback to model some important empirical results; and (4) problematic linking hypotheses between crucial simulations and behavioral data.
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