Voice for All: Evaluating the Accuracy and Equity of Automatic Speech Recognition Systems in Transcribing Patient Communications in Home Healthcare

Xu, Z., Vergez, S., Esmaeili, E., Zolnour, A., Briggs, K. A., Scroggins, J. K., Hosseini Ebrahimabad, S. F., Noble, J. M., Topaz, M., Bakken, S., Bowles, K. H., Spens, I., Onorato, N., Sridharan, S., McDonald, M. V., & Zolnoori, M. (2025). Voice for All: Evaluating the Accuracy and Equity of Automatic Speech Recognition Systems in Transcribing Patient Communications in Home Healthcare. MEDINFO 2025 — Healthcare Smart × Medicine Deep. https://doi.org/10.3233/shti251273
Authors:
Zidu Xu
Sasha Vergez
Elyas Esmaeili
Ali Zolnour
Krystal Anne Briggs
Jihye Kim Scroggins
Seyed Farid Hosseini Ebrahimabad
James M Noble
Maxim Topaz
Suzanne Bakken
Kathryn H Bowles
Ian Spens
Nicole Onorato
Sridevi Sridharan
Margaret V McDonald
Maryam Zolnoori
Affiliated Authors:
Zidu Xu
Elyas Esmaeili
Ali Zolnour
Krystal Anne Briggs
Jihye Kim Scroggins
James M Noble
Maxim Topaz
Suzanne Bakken
Maryam Zolnoori
Columbia Affiliation:
Subjects:
Speech Recognition Software (MeSH)
Home Care Services (MeSH)
Author Keywords:
automatic speech recognition systems
home healthcare
transcription disparities
automatic speech recognition
electronic health record
home care
human
natural language processing
electronic health records
home care services
humans
speech recognition software
elink
Publication Type:
Article
Unique ID:
10.3233/shti251273
PMID:
40776290
DOI:
10.3233/shti251273
Journal:
Studies in Health Technology and Informatics
Publication Date:
Data Source:
PubMed
Source Link:
View PubMed Record
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