Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

10-2024

Abstract

In social service centers, practitioners engage in conversations with clients with dementia to facilitate their daily activities and provide support when they are distressed. However, the nature of the care demands the practitioner’s active engagement, which becomes difficult to deliver as the number of people who need care expands. Researchers have been investigating the efficacy of developing agents that assume conversational tasks to alleviate this work. To contribute to the future design of agents for caregiving, we collected and analyzed ten conversations between clients with mild dementia and practitioners who provide care. Our analyses of turn-taking dynamics and dialogue acts with 15k utterances uncovered patterns such as noticeable differences in clients’ and practitioners’ conversational dynamics and the prevalence of neutral-toned, question-oriented utterances by practitioners. We then prototyped a large language model-based script that generates responses to client utterances. We found potential approaches and challenges for making its utterance pattern more similar to that of a practitioner.

Discipline

Artificial Intelligence and Robotics | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility

Identifier

https://doi.org/10.1145/3663548.3688523

Publisher

ACM

City or Country

New York

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