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

要旨

With the recent advancements in intelligent personal assistants (IPAs), their popularity is rapidly increasing when it comes to utilizing Automatic Speech Recognition within households. In this study, we used a Wizard-of-Oz methodology to evaluate and compare the usability of American Sign Language (ASL), Tap to Alexa, and smart home apps among 23 deaf participants within a limited-domain smart home environment. Results indicate a slight usability preference for ASL. Linguistic analysis of the participants' signing reveals a diverse range of expressions and vocabulary as they interacted with IPAs in the context of a restricted-domain application. On average, deaf participants exhibited a vocabulary of 47 +/- 17 signs with an additional 10 +/- 7 fingerspelled words, for a total of 246 different signs and 93 different fingerspelled words across all participants. We discuss the implications for the design of limited-vocabulary applications as a stepping-stone toward general-purpose ASL recognition in the future.

著者
Nina Tran
Gallaudet University, Washington, District of Columbia, United States
Paige S. DeVries
Gallaudet University , Washington, District of Columbia, United States
Matthew Seita
Gallaudet University, Washington, District of Columbia, United States
Raja Kushalnagar
Gallaudet University, Washington, District of Columbia, United States
Abraham Glasser
Gallaudet University, Washington, District of Columbia, United States
Christian Vogler
Gallaudet University , Washington , District of Columbia, United States
論文URL

https://doi.org/10.1145/3613904.3642094

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Assistive Interactions: Solutions for d/Deaf and Hard of Hearing Users

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5 件の発表
2024-05-15 20:00:00
2024-05-15 21:20:00