An amorphous model for morphological processing in visual comprehension based on naive discriminative learning.

By R. Harald Baayen, Petar Milin, Dušica Filipović Đurđević, Peter Hendrix, Marco Marelli. Psychology Review, 2011

524 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Developmental and Educational Psychology, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/3725bc645326f8b63480405ff5781770c60edeb4

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In Cognitive Neuroscience

In Developmental and Educational Psychology

In Experimental and Cognitive Psychology

Citations in the corpus

Making choices in Russian: pros and cons of statistical methods for rival forms (2013, background): “Baayen et al. (2011) showed that a simple naive discrimination network can account for a wide range of empirical ndings in the literature on lexical processing.”
Subtlex-UK: A New and Improved Word Frequency Database for British English (2014, background): “Because extra information can be obtained from word combinations (Arnon & Snider, 2010; Baayen, Milin, Filipovic Durdevic, Hendrix, & Marelli, 2011; Siyanova-Chanturia, Conklin, & van Heuven, 2011), we also collected word bigram frequencies in the entire corpus (i.e., the frequency with which word…”
Frequency in lexical processing (2016, background): “The model correctly predicts both whole-word frequency effects and constituent frequency effects for English (Baayen et al., 2011) as well as for Vietnamese (Pham, 2014).”
Error and expectation in language learning: The curious absence of mouses in adult speech (2013, background): “…adults(Stemberger2004,Stemberger&Middleton2003,Tabaketal.2010;seealso Baayenetal.2011,Bannardetal.2009,Ramscar,Dye,&Klein2013),orthatyounger adultsprocesslanguageinthesamewayasolderadults(Ramscar,Hendrix,etal.2013).”
Choosing prediction over explanation in psychology: Lessons from machine learning (2017, background): “…the production of new models that explain ever more variance in behavioral tasks like word naming has been guided by, and reciprocally informs, psycholinguistic theory (e.g., Baayen, Milin, Đurdˉevic´, Hendrix, & Marelli, 2011; Perry, Ziegler, & Zorzi, 2010; Yap, Balota, Sibley, & Ratcliff, 2012).”
The Myth of Cognitive Decline: Non-Linear Dynamics of Lifelong Learning (2014, methodology): “…judgments, simulated lexical decision times (SRTs) for each of the words in the Balota et al. test set were estimated as a function of the activations in the NDR models given the ngram cues in the input words (Baayen et al., 2011; a more detailed description of the method is given in the Appendix).”
Weighing up the evidence for sound symbolism: Distributional properties predict cue strength (2017, background): “This may be the case because some form-meaning relationships may arise purely by chance, which (following the assumptions of Baayen et al., 2011) allows that such systematic relationships are likely to arise, but has nothing to say about which relationships they will be. There may be no answer to th”
Demythologizing the word frequency effect: A discriminative learning perspective (2010, methodology): “To address this question, the predictions of two computational models for reading were compared: the cascaded dual rout model (DRC) of Coltheart et al. (2001), and the Naive Discriminative Reader model of Baayen et al. (2010).”