Segment-Based Signal Typing and Predictive Modeling in Pediatric Dysphonia With Different Vibratory Sources
The manual signal typing tool developed in this study shows promise for improving the precision of signal typing, which may enhance the reliability of conventional acoustic measures and enable the calculation of signal type proportions as potential outcome metrics. Automating signal typing using the measures investigated in this study could further increase the clinical utility of this tool by providing objective signal typing.
Authors
- Barbara Weinrich (ORCID: https://orcid.org/0000-0001-5373-812X)
- Supraja Anand (ORCID: https://orcid.org/0009-0007-1116-1650)
- Alessandro de Alarcón (ORCID: https://orcid.org/0000-0003-4792-4676)
- Yeonggwang Park
- Susan Baker Brehm (ORCID: https://orcid.org/0000-0002-4039-7052)
- Lisa Kelchner (ORCID: https://orcid.org/0000-0002-1592-4113)
- David A. Eddins (ORCID: https://orcid.org/0000-0003-3716-2436)
- Rahul Shrivastav
Institutions
- University of Central Florida (US)
- Cincinnati Children's Hospital Medical Center (US)
- University of South Florida (US)
- Indiana University Bloomington (US)
- University of Cincinnati (US)
- Miami University (US)
Publication Details
- Journal
- Journal of Speech Language and Hearing Research
- Published
- 2025-10-30
- DOI
- https://doi.org/10.1044/2025_jslhr-25-00264
- Primary Topic
- Voice and Speech Disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00