Discourse Behavior of Older Adults Interacting with a Dialogue Agent Competent in Multiple Topics
| Autor: | S. Zahra Razavi, Lenhart K. Schubert, Kimberly van Orden, Mohammad Rafayet Ali, Benjamin Kane, Ehsan Hoque |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | ACM Transactions on Interactive Intelligent Systems. 12:1-21 |
| ISSN: | 2160-6463 2160-6455 |
| DOI: | 10.1145/3484510 |
| Popis: | We present a conversational agent designed to provide realistic conversational practice to older adults at risk of isolation or social anxiety, and show the results of a content analysis on a corpus of data collected from experiments with elderly patients interacting with our system. The conversational agent, represented by a virtual avatar, is designed to hold multiple sessions of casual conversation with older adults. Throughout each interaction, the system analyzes the prosodic and nonverbal behavior of users and provides feedback to the user in the form of periodic comments and suggestions on how to improve. Our avatar is unique in its ability to hold natural dialogues on a wide range of everyday topics—27 topics in three groups, developed in collaboration with a team of gerontologists. The three groups vary in “degrees of intimacy,” and as such in degrees of cognitive difficulty for the user. After collecting data from nine participants who interacted with the avatar for seven to nine sessions over a period of 3 to 4 weeks, we present results concerning dialogue behavior and inferred sentiment of the users. Analysis of the dialogues reveals correlations such as greater elaborateness for more difficult topics, increasing elaborateness with successive sessions, stronger sentiments in topics concerned with life goals rather than routine activities, and stronger self-disclosure for more intimate topics. In addition to their intrinsic interest, these results also reflect positively on the sophistication and practical applicability of our dialogue system. |
| Databáze: | OpenAIRE |
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