Various technologies mediate synchronous audio-visual one-on-one communication (SAVOC) between Deaf and Hard-of-Hearing (DHH) and hearing colleagues, including automatic-captioning smartphone apps for in-person settings, or text-chat features of videoconferencing software in remote settings. Speech and non-verbal behaviors of hearing speakers, e.g. speaking too quietly, can make SAVOC difficult for DHH users, but prior work had not examined technology-mediated contexts. In an in-person study (N=20) with an automatic captioning smartphone app, variations in a hearing actor's enunciation and intonation dynamics affected DHH users' satisfaction. In a remote study (N=23) using a videoconferencing platform with text chat, variations in speech rate, voice intensity, enunciation, intonation dynamics, and eye contact led to such differences. This work contributes empirical evidence that specific behaviors of hearing speakers affect the accessibility of technology-mediated SAVOC for DHH users, providing motivation for future work on detecting or encouraging useful communication behaviors among hearing individuals.
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A Classroom Accessibility Analysis App for Deaf Students
Deaf and hard of hearing (DHH) individuals do not have equal access to audio information in most educational settings, even with visual translation accommodations such as sign language interpreters or captioners. As a result, their learning and retention rates lag behind in comparison with their hearing peers. Research shows DHH individuals lose lecture information due to two main factors largely unaddressed by the traditional accommodations: 1) increased cognitive load associated with processing the visual translation of audio simultaneously with other visual information sources, and 2) visual attention limits associated with viewing layouts that have widely dispersed visuals that may be far away or at awkward viewing angles. We discuss the impact of architectural visuals on the DHH student, accommodation team and discuss an automatic measure of a simple accessibility app and scale using face and body identification from a 360-degree video snapshot.
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- Award ID(s):
- 1757836
- PAR ID:
- 10132487
- Date Published:
- Journal Name:
- ASSETS '19: The 21st International ACM SIGACCESS Conference on Computers and Accessibility
- Page Range / eLocation ID:
- 569 to 571
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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