Automated Scoring of the Speech Intelligibility Test Using Autoscore
Overall, SIT-extended Autoscore performed as well as human scorers and substantially improved scoring accuracy relative to the original version of Autoscore. Coupled with the substantial time and effort saving provided by Autoscore, its utility has been strengthened by the extensions developed and tested here.
Authors
- Tyson S. Barrett (ORCID: https://orcid.org/0000-0002-2137-1391)
- Kaila L. Stipancic (ORCID: https://orcid.org/0000-0001-5185-563X)
- Stephanie A. Borrie (ORCID: https://orcid.org/0000-0002-2336-0071)
- Kris Tjaden (ORCID: https://orcid.org/0000-0003-0971-7449)
Institutions
- Utah State University (US)
- University at Buffalo, State University of New York (US)
Publication Details
- Journal
- American Journal of Speech-Language Pathology
- Published
- 2024-12-12
- DOI
- https://doi.org/10.1044/2024_ajslp-24-00276
- Citations
- 3
- Primary Topic
- Speech Recognition and Synthesis
- Type
- article
- Field-Weighted Citation Impact
- 1.04
Funders
- Utah State University
- MGH Institute of Health Professions
- National Institute on Deafness and Other Communication Disorders