research-article

TalkTive: A Conversational Agent Using Backchannels to Engage Older Adults in Neurocognitive Disorders Screening

Authors:

Tinky Oi Ting HO,

Xiaojuan MaAuthors Info & Claims

CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Article No.: 304, Pages 1 - 19

https://doi.org/10.1145/3491102.3502005

Published: 29 April 2022 Publication History

Abstract

Conversational agents (CAs) have the great potential in mitigating the clinicians’ burden in screening for neurocognitive disorders among older adults. It is important, therefore, to develop CAs that can be engaging, to elicit conversational speech input from older adult participants for supporting assessment of cognitive abilities. As an initial step, this paper presents research in developing the backchanneling ability in CAs in the form of a verbal response to engage the speaker. We analyzed 246 conversations of cognitive assessments between older adults and human assessors, and derived the categories of reactive backchannels (e.g. “hmm”) and proactive backchannels (e.g. “please keep going”). This is used in the development of TalkTive, a CA which can predict both timing and form of backchanneling during cognitive assessments. The study then invited 36 older adult participants to evaluate the backchanneling feature. Results show that proactive backchanneling is more appreciated by participants than reactive backchanneling.

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Index Terms

TalkTive: A Conversational Agent Using Backchannels to Engage Older Adults in Neurocognitive Disorders Screening
1. Human-centered computing
  1. Human computer interaction (HCI)
  2. Interaction design
    1. Empirical studies in interaction design

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cover image ACM Conferences

CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

April 2022

10459 pages

ISBN:9781450391573

DOI:10.1145/3491102

Editors:
Simone Barbosa
PUC-Rio, Brazil
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Cliff Lampe
University of Michigan, USA
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Caroline Appert
Université Paris-Saclay, France
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David A. Shamma
Toyota Research Institute, USA
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Steven Drucker
Microsoft Research, USA
,
Julie Williamson
University of Glasgow, UK
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Koji Yatani
University of Tokyo, Japan

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ACM CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

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Kim DKim MYun S(2024)The Impact of Backchannel in Medical-Questionnaire Robot on User PerceptionJournal of information and communication convergence engineering10.56977/jicce.2024.22.4.32222:4(322-329)Online publication date: 31-Dec-2024
https://doi.org/10.56977/jicce.2024.22.4.322
Qian ZFu JZhou Y(2024)Gaining Technological Autonomy and Soci-emotional Support: A Case Study of How and Why Chinese Older Adults Engage with a Semi-acquaintance Online CommunityProceedings of the ACM on Human-Computer Interaction10.1145/36869808:CSCW2(1-35)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686980
Ding Z(2024)Advancing GUI for Generative AI: Charting the Design Space of Human-AI Interactions through Task Creativity and ComplexityCompanion Proceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640544.3645241(140-143)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640544.3645241
Prinos KPatwari NPower C(2024)Speaking of accent: A content analysis of accent misconceptions in ASR researchProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3658969(1245-1254)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3630106.3658969
Qian ZFu JZhou Y(2024)Overcoming Barriers, Achieving Goals: A Case Study of an Older User's Technology AutonomyExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3637150(1-7)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3637150
Hu JLi JZeng YYang DLiang DMeng HMa X(2024)Designing Scaffolding Strategies for Conversational Agents in Dialog Task of Neurocognitive Disorders ScreeningProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642960(1-21)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642960
Kim YKang YKim BKim JKim G(2024)Exploring the role of engagement and adherence in chatbot-based cognitive training for older adults: memory function and mental health outcomesBehaviour & Information Technology10.1080/0144929X.2024.2362406(1-13)Online publication date: 10-Jun-2024
https://doi.org/10.1080/0144929X.2024.2362406
Kim SJung HThao S(2024)Communication, Socialization, and Literacy for Adults With Developmental Disabilities: An Interview Study of Parents' Perspectives and ExperiencesAmerican Journal of Speech-Language Pathology10.1044/2024_AJSLP-24-0017733:6(3051-3068)Online publication date: 4-Nov-2024
https://doi.org/10.1044/2024_AJSLP-24-00177
Woo JShidara KAchard CTanaka HNakamura SPelachaud C(2024)Adaptive virtual agentInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2024.103321190:COnline publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.ijhcs.2024.103321
Gratch J(2023)The promise and peril of interactive embodied agents for studying non-verbal communication: a machine learning perspectivePhilosophical Transactions of the Royal Society B: Biological Sciences10.1098/rstb.2021.0475378:1875Online publication date: 6-Mar-2023
https://doi.org/10.1098/rstb.2021.0475
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