Remotely Co-Designing Features for Communication Applications using Automatic Captioning with Deaf and Hearing Pairs

要旨

Deaf and Hard-of-Hearing (DHH) users face accessibility challenges during in-person and remote meetings. While emerging use of applications incorporating automatic speech recognition (ASR) is promising, more user-interface and user-experience research is needed. While co-design methods could elucidate designs for such applications, COVID-19 has interrupted in-person research. This study describes a novel methodology for conducting online co-design workshops with 18 DHH and hearing participant pairs to investigate ASR-supported mobile and videoconferencing technologies along two design dimensions: Correcting errors in ASR output and implementing notification systems for influencing speaker behaviors. Our methodological findings include an analysis of communication modalities and strategies participants used, use of an online collaborative whiteboarding tool, and how participants reconciled differences in ideas. Finally, we present guidelines for researchers interested in online DHH co-design methodologies, enabling greater geographically diversity among study participants even beyond the current pandemic.

受賞
Honorable Mention
著者
Matthew Seita
Rochester Institute of Technology, Rochester, New York, United States
Sooyeon Lee
Rochester Institute of Technology, Rochester, New York, United States
Sarah Andrew
Rochester Institute of Technology, Rochester, New York, United States
Kristen Shinohara
Rochester Institute of Technology, Rochester, New York, United States
Matt Huenerfauth
Rochester Institute of Technology, Rochester, New York, United States
論文URL

https://dl.acm.org/doi/abs/10.1145/3491102.3501843

動画

会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)

セッション: Captioning Images, Videos and Applications

293
4 件の発表
2022-05-05 01:15:00
2022-05-05 02:30:00