Date of Completion
Spring 5-1-2021
Thesis Advisor(s)
James S. Magnuson
Honors Major
Speech, Language and Hearing Sciences
Abstract
TRACE is one of the most successful models of spoken word recognition and has been used to account for a number of patterns in human spoken word processing. TRACE was originally implemented in the C programming language (McClelland & Elman, 1986). To make it more accessible, it was reimplemented in Java (Strauss et. al., 2007). Our team is currently reimplementing TRACE in JavaScript. The JavaScript version of TRACE, or jsTRACE, is an update to the code that avoids obsolete (or nearly obsolete) modules and libraries, and will allow users to do batch simulations with great flexibility, since they can just write JavaScript code. This project focused on developing and demonstrating methods for batch scripting. Simulation results from an example batch script were used to explore a theoretical debate in spoken word recognition and show how feedback from lexical to phonemic representations in the model facilitates word recognition.
Recommended Citation
Grubb, Samantha, "Methodological and Theoretical Extensions to the TRACE Model of Spoken Word Recognition" (2021). Honors Scholar Theses. 794.
https://digitalcommons.lib.uconn.edu/srhonors_theses/794