PROCEEDINGS OF THE 27TH INTERNATIONAL ACM SIGACCESS CONFERENCE ON COMPUTERS AND ACCESSIBILITY, ASSETS 2025(2025)
Tulane Univ
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摘要
dDeaf and Hard of Hearing (DHH) people often face significant barriers in medical settings, leading to miscommunication and reduced access to care. While American Sign Language (ASL) interpretation is essential for effective communication with DHH signers, it is frequently unavailable in emergency contexts. Emergency Medical Responders (EMRs)-frontline responders trained to deliver basic emergency care-often struggle to obtain accurate medical histories, particularly from DHH people with limited English literacy. To address this, we designed an AI-based ASL learning tool tailored for EMRs, featuring medical vocabulary modules and AI-powered vocabulary testing support. We present a preliminary evaluation of the tool with five EMRs and publicly release a working prototype with this paper. Insights from the study inform new features and vocabulary expansion.
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关键词
American Sign Language,Sign Language,ASL,Sign Language,Learning,Emergency Medical Services,Emergency Medical Responders,EMR,EMS,EMT,Vocabulary Learning,Dictionary,Communication,in Emergency Settings,First Aid,Healthcare