Assessment of Sign Language-Based versus Touch-Based Input for Deaf Users Interacting with Intelligent Personal Assistants
<|reference_start|>Assessment of Sign Language-Based versus Touch-Based Input for Deaf Users Interacting with Intelligent Personal Assistants: 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.<|reference_end|>
@article{tran2024assessment,
    title={Assessment of Sign Language-Based versus Touch-Based Input for Deaf
  Users Interacting with Intelligent Personal Assistants},
    author={Nina Tran, Paige DeVries, Matthew Seita, Raja Kushalnagar, Abraham
  Glasser and Christian Vogler},
    journal={arXiv preprint arXiv:2404.14605},
    year={2024},
    doi={10.1145/3613904.3642094},
    archivePrefix={arXiv},
    eprint={2404.14605},
    primaryClass={cs.HC}
}