Time Invariant String Kernel Model

Authors: Heejo YouThomas HannaganJames Magnuson
Updated: Fri 15 December 2017
Source: https://github.com/maglab-uconn/TISK1.0
Type: Github repository, Python code
Languages: English
Keywords: word-recognitionphoneticspythonEnglish
Open Access: yes
License:
Documentation: https://github.com/maglab-uconn/TISK1.0/blob/master/README.md
Publications: Hannagan, T., Magnuson, J., Grainger, J. (2013). Spoken word recognition without a TRACE. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2013.00563
Citation: You, H., Magnuson, J.S. (2018). TISK 1.0: An easy-to-use Python implementation of the time-invariant string kernel model of spoken word recognition. Behavior Research Methods. 50, 871–889. https://doi.org/10.3758/s13428-017-1012-5
Summary:

TISK is the Time Invariant String Model of (human) spoken word recognition. It is an interactive-activation model similar to the TRACE model (McClelland & Elman in Cognitive Psychology, 18, 1–86, 1986), but TISK replaces most of TRACE’s reduplicated, time-specific nodes with theoretically motivated time-invariant, open-diphone nodes.