Towards More Transactional Voice Assistants: Investigating the Potential for a Multimodal Voice-Activated Indoor Navigation Assistant for Blind and Sighted Travelers

要旨

Voice assistants (VAs) – like Amazon Alexa or Siri – offer hands-/eyes-free interactions that are beneficial to a range of users, including individuals who are blind, to fulfill tasks that are otherwise difficult or inaccessible. While these interfaces model conversational interactions to achieve simple tasks, there have been recent calls for VAs that model more transactional interactions for a wider range of complex activities. In this study, we explored the extension of VAs’ capabilities in the context of indoor navigation through mixed-ability focus groups with blind and sighted airport travelers. We found high overlap in the difficulties encountered by blind and sighted travelers, as well as shared interest in a voice-activated travel assistant to improve travel experiences. Leveraging user-elicited recommendations, we present interaction design examples that showcase customization of different and multiple modalities, which collectively demonstrate how VAs can more broadly achieve transactional interactions in complex task scenarios.

著者
Ali Abdolrahmani
University of Maryland, Baltimore County, Baltimore, Maryland, United States
Maya Howes. Gupta
University of California, Irvine, Irvine, California, United States
Mei-Lian Vader
UMBC, Baltimore, Maryland, United States
Ravi Kuber
UMBC, Baltimore, Maryland, United States
Stacy Branham
University of California, Irvine, Irvine, California, United States
DOI

10.1145/3411764.3445638

論文URL

https://doi.org/10.1145/3411764.3445638

動画

会議: CHI 2021

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)

セッション: Accessible Interaction

[A] Paper Room 01, 2021-05-13 17:00:00~2021-05-13 19:00:00 / [B] Paper Room 01, 2021-05-14 01:00:00~2021-05-14 03:00:00 / [C] Paper Room 01, 2021-05-14 09:00:00~2021-05-14 11:00:00
Paper Room 01
12 件の発表
2021-05-13 17:00:00
2021-05-13 19:00:00
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