• Microsoft AI for Accessibility launched sign language workshop, attracting top researchers. • PhD student Abraham Glasser received 3‑year grant to enhance ASL interaction with smart assistants. • RIT’s CAIR team studies Deaf and Hard‑of‑Hearing users’ preferences for home‑assistant interfaces. • Current assistants rely on voice; none understand sign language, leaving a large untapped market. • Research explores camera‑based sign detection, processing, and visual response on household devices. • Goal: drive inclusion, broaden AI accessibility, and empower sign‑language users at home.
Article Summaries:
- Rochester Institute of Technology’s AI for Accessibility program awarded a three‑year grant to Ph.D. student Abraham Glasser to explore how American Sign Language (ASL) users can interact with home‑based smart assistants. Glasser, a native ASL signer, works at the Center for Accessibility and Inclusion Research (CAIR) to investigate how Deaf and hard‑of‑hearing (DHH) users prefer to activate and issue commands to voice‑controlled devices that now also feature cameras and screens. Using a Wizard‑of‑Oz videoconference setup, the team recorded DHH participants signing to a device while an unseen interpreter voiced the commands in English. Analysis revealed new interaction patterns, such as distinct wake‑up signals, and highlighted the need for more sign‑language data to enable future ASL‑capable assistants.
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