Computational modelling of an auditory lexical decision experiment using jTRACE and TISK
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We present a series of computational simulations of the auditory lexical decision task using the jTRACE and TISK models of spoken word recognition. Simulation 1 replicates high accuracy in word recognition and similar performance of these models using the small, default dictionary. Simulation 2 expands the set of words and phonemes, leading to issues in representing certain phonemes in jTRACE. Simulation 3 expands the lexicon of competitors and we find that TISK struggles to select the target word as the winner. Finally, Simulation 4 shows that the decision criteria employed leads to many false positives when pseudowords are presented to the model. None of the model estimates of the time cycle when the winner should be selected predicted participant response latency in the auditory lexical decision task. We discuss these findings and offer suggestions as to what a contemporary model of spoken word recognition should be able to do.
Supplementary material including simulation code is available here: https://doi.org/10.7939/r3-52m3-a502.
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http://purl.org/coar/resource_type/c_6501 http://purl.org/coar/version/c_970fb48d4fbd8a85
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https://doi.org/10.1080/23273798.2020.1764600
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en