Voice assistants embodied in smart speakers (e.g., Amazon Echo, Google Home) enable conversational interaction that does not necessarily rely on expertise with mobile or desktop computing. Hence, these voice assistants offer new opportunities to different populations, including individuals who are not interested or able to use traditional computing devices such as computers and smartphones. To understand how older adults who use technology infrequently perceive and use these voice assistants, we conducted a three-week field deployment of the Amazon Echo Dot in the homes of seven older adults. Participants described increased confidence using digital technology and found the conversational voice interfaces easy to use. While some types of usage dropped over the three-week period (e.g., playing music), we observed consistent usage for finding online information. Given that much of this information was health-related, this finding emphasizes the need to revisit concerns about credibility of information with this new interaction medium. Although features to support memory (e.g., setting timers, reminders) were initially perceived as useful, the actual usage was unexpectedly low due to reliability concerns. We discuss how these findings apply to other user groups along with design implications and recommendations for future work on voice user interfaces.
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Data Capture and Analyses from Conversational Devices in the Homes of the Elderly.
Conversational devices such as Amazon Echo and Google Home represent more than a way to tap into the behavioral surplus of consumers. They provide an opportunity to address societal problems by examining data streams produced by these devices. In this paper, we describe usage patterns and problems related to the use of Amazon Echo devices at home by one specific demographic: the elderly. We rely on a pilot project to collect usage data over multiple months based on deployment of these devices in the homes of eight elderly individuals who either live alone or with a spouse. The paper describes methods used to ensure confidentiality, data collection and analysis procedures, and our findings. We find that the use of conversational devices remains restricted to single commands instead of conversations, making yourself understood remains a problem, sustained use remains a challenge, and the interaction rarely goes beyond simple commands. We interpret the results, and point to the potential for such devices in the lives of the elderly, specifically for health-related problems. The paper also describes lessons learned for capture and analysis of data from such conversational devices.
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- Award ID(s):
- 1641148
- PAR ID:
- 10276952
- Editor(s):
- Guizzardi, G.; Gailly, F.; Suzana, P.
- Date Published:
- Journal Name:
- Advances in Conceptual Modeling. ER 2019. Lecture Notes in Computer Science.
- Volume:
- 11787
- Page Range / eLocation ID:
- 157-166
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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