Computational modelling of an auditory lexical decision experiment using jTRACE and TISK

ABSTRACT

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.

KEYWORDS:

• Spoken word recognition
• auditory lexical decision task
• computational modelling
• TRACE
• TISK

Acknowledgements

We thank Matthew C. Kelley for programming assistance and fruitful discussions regarding the paper topic. We thank Julien Mayor for sharing his simulation material and insights. We thank one anonymous reviewer and James McQueen for their helpful comments that improved the quality of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This project was funded by the Social Sciences and Humanities Research Council of Canada [grant number 435-2014-0678].