Time Invariant String Kernel Model
| Authors: | Heejo You, Thomas Hannagan, James Magnuson |
|---|---|
| Updated: | Fri 15 December 2017 |
| Source: | https://github.com/maglab-uconn/TISK1.0 |
| Type: | Github repository, Python code |
| Languages: | English |
| Keywords: | word-recognition, phonetics, python, English |
| 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. |