activity
20192026
most citedAssessment of Sign Language-Based versus Touch-Based Input for Deaf Users Interacting with Intelligent Personal Assistants

20 citations · 50 across the 9 of their papers we have counts for

collaborators

9 papers

cs.HC2026

Are Caption Metrics Broken? Latency, Deaf and Hard of Hearing User Ratings, and Bias across Technologies

Bernard Thompson, James Waller, Luz Fanny Calderon Torres +5

Live captions on TV often contain errors and timing issues, making it hard for deaf and hard-of-hearing (DHH) viewers to follow dialog. It is essential that caption quality metrics…

cs.CL2026

DiscoSign: Discourse-Aware Text to Sign Language Gloss Translation

Vasileios Baltatzis, Mert Inan, Connor Gillis +4

Sign language processing systems have traditionally operated at the sentence level, ignoring critical discourse phenomena fundamental to sign language comprehension. We introduce D…

cs.HC2026

Deaf and Hard of Hearing Access to Intelligent Personal Assistants: Comparison of Voice-Based Options with an LLM-Powered Touch Interface

Paige S. DeVries, Michaela Okosi, Ming Li +6

We investigate intelligent personal assistants (IPAs) accessibility for deaf and hard of hearing (DHH) people who can use their voice in everyday communication. The inability of IP…

cs.HC2025

Barriers to Employment: The Deaf Multimedia Authoring Tax

C. Vogler, A. Glasser, R. Kushalnagar +7

This paper describes the challenges that deaf and hard of hearing people face with creating accessible multimedia content, such as portfolios, instructional videos and video presen…

cs.HC2025

Towards AI-driven Sign Language Generation with Non-manual Markers

Han Zhang, Rotem Shalev-Arkushin, Vasileios Baltatzis +7

Sign languages are essential for the Deaf and Hard-of-Hearing (DHH) community. Sign language generation systems have the potential to support communication by translating from writ…

cs.HC2024★ 20 cited

Assessment of Sign Language-Based versus Touch-Based Input for Deaf Users Interacting with Intelligent Personal Assistants

Nina Tran, Paige DeVries, Matthew Seita +3

With the recent advancements in intelligent personal assistants (IPAs), their popularity is rapidly increasing when it comes to utilizing Automatic Speech Recognition within househ…

cs.HC2024★ 15 cited

How Users Experience Closed Captions on Live Television: Quality Metrics Remain a Challenge

Mariana Arroyo Chavez, Molly Feanny, Matthew Seita +6

This paper presents a mixed methods study on how deaf, hard of hearing and hearing viewers perceive live TV caption quality with captioned video stimuli designed to mirror TV capti…

cs.HC2024★ 4 cited

Sign Language-Based versus Touch-Based Input for Deaf Users with Interactive Personal Assistants in Simulated Kitchen Environments

Paige DeVries, Nina Tran, Keith Delk +6

In this study, we assess the usability of interactive personal assistants (IPAs), such as Amazon Alexa, in a simulated kitchen smart home environment, with deaf and hard of hearing…

cs.HC2019★ 11 cited

Closed ASL Interpreting for Online Videos

Raja Kushalnagar, Matthew Seita, Abraham Glasser

Deaf individuals face great challenges in today's society. It can be very difficult to be able to understand different forms of media without a sense of hearing. Many videos and mo…