15 found
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  1.  24
    The Time Course of Spoken Word Learning and Recognition: Studies with Artificial Lexicons.James S. Magnuson, Michael K. Tanenhaus, Richard N. Aslin & Delphine Dahan - 2003 - Journal of Experimental Psychology: General 132 (2):202.
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  2.  7
    The Dynamics of Lexical Competition During Spoken Word Recognition.James S. Magnuson, James A. Dixon, Michael K. Tanenhaus & Richard N. Aslin - 2007 - Cognitive Science 31 (1):133-156.
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  3.  42
    The Time Course of Anticipatory Constraint Integration.Anuenue Kukona, Shin-Yi Fang, Karen A. Aicher, Helen Chen & James S. Magnuson - 2011 - Cognition 119 (1):23-42.
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  4.  4
    Spoken Word Recognition Without a TRACE.Thomas Hannagan, James S. Magnuson & Jonathan Grainger - 2013 - Frontiers in Psychology 4.
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  5.  14
    Which Words Compete? The Dynamics of Similarity During Spoken Word Recognition.James S. Magnuson, J. Dixon, M. K. Tanenhaus & R. N. Aslin - 2007 - Cognitive Science 31 (1).
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  6.  13
    Immediate Effects of Form-Class Constraints on Spoken Word Recognition.James S. Magnuson, Michael K. Tanenhaus & Richard N. Aslin - 2008 - Cognition 108 (3):866-873.
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  7.  17
    Lexical Effects on Compensation for Coarticulation: The Ghost of Christmash Past.James S. Magnuson, Bob McMurray, Michael K. Tanenhaus & Richard N. Aslin - 2003 - Cognitive Science 27 (2):285-298.
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  8.  13
    The Link Between Statistical Segmentation and Word Learning in Adults.Daniel Mirman, James S. Magnuson, Katharine Graf Estes & James A. Dixon - 2008 - Cognition 108 (1):271-280.
  9.  22
    Interaction in Spoken Word Recognition Models: Feedback Helps.James S. Magnuson, Daniel Mirman, Sahil Luthra, Ted Strauss & Harlan D. Harris - 2018 - Frontiers in Psychology 9.
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  10.  15
    Effects of Attention on the Strength of Lexical Influences on Speech Perception: Behavioral Experiments and Computational Mechanisms.Daniel Mirman, James L. McClelland, Lori L. Holt & James S. Magnuson - 2008 - Cognitive Science 32 (2):398-417.
  11.  14
    Lexical Effects on Compensation for Coarticulation: A Tale of Two Systems?James S. Magnuson, Bob McMurray, Michael K. Tanenhaus & Richard N. Aslin - 2003 - Cognitive Science 27 (5):801-805.
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  12.  18
    Breaking Down the Bilingual Cost in Speech Production.Jasmin Sadat, Clara D. Martin, James S. Magnuson, François‐Xavier Alario & Albert Costa - 2016 - Cognitive Science 40 (8):1911-1940.
    Bilinguals have been shown to perform worse than monolinguals in a variety of verbal tasks. This study investigated this bilingual verbal cost in a large-scale picture-naming study conducted in Spanish. We explored how individual characteristics of the participants and the linguistic properties of the words being spoken influence this performance cost. In particular, we focused on the contributions of lexical frequency and phonological similarity across translations. The naming performance of Spanish-Catalan bilinguals speaking in their dominant and non-dominant language was compared (...)
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  13.  1
    EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition.James S. Magnuson, Heejo You, Sahil Luthra, Monica Li, Hosung Nam, Monty Escabí, Kevin Brown, Paul D. Allopenna, Rachel M. Theodore, Nicholas Monto & Jay G. Rueckl - 2020 - Cognitive Science 44 (4).
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  14.  18
    Effect of Representational Distance Between Meanings on Recognition of Ambiguous Spoken Words.Daniel Mirman, Ted J. Strauss, James A. Dixon & James S. Magnuson - 2010 - Cognitive Science 34 (1):161-173.
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  15.  14
    No Compelling Evidence Against Feedback in Spoken Word Recognition.Michael K. Tanenhaus, James S. Magnuson, Bob McMurray & Richard N. Aslin - 2000 - 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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