Effectiveness of Conversational Robots Capable of Estimating and Modeling User Values

Sakamoto, Yuki; Uchida, Takahisa; Ishiguro, Hiroshi

doi:https://doi.org/10.1007/s12369-025-01258-x

Effectiveness of Conversational Robots Capable of Estimating and Modeling User Values

Sakamoto, Yuki; Uchida, Takahisa; Ishiguro, Hiroshi

International Journal of Social Robotics, 2025, 17, 1003-1017

アクセス数:11件（2025-07-30 09:27 集計）

固定URL: https://hdl.handle.net/11094/102251

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タイトル	Effectiveness of Conversational Robots Capable of Estimating and Modeling User Values
著者	著者名 Sakamoto, Yuki
	NRID 1000030906417 1000030906417 researchmap permalink TakahisaUchida TakahisaUchida Scopus Author ID 57191886812 57191886812 著者名 Uchida, Takahisa
	NRID 1000010232282 1000010232282 ORCID 0000-0002-0805-7648 0000-0002-0805-7648 researchmap permalink read0013747 read0013747 Scopus Author ID 26643316500 26643316500 著者名 Ishiguro, Hiroshi
キーワード等	Conversational robot
	Human values
	Human-robot interaction (HRI)
	Personalization
内容	The version of record of this article, first published in International Journal of Social Robotics, is available online at Publisher’s website: https://doi.org/10.1007/s12369-025-01258-x.
抄録	Personalizing a dialogue system according to the user has been recognized to have various positive effects. Despite the significance of user values, concepts guiding choices and evaluations being recognized in communication, they have not been considered in personalized dialogue systems. Therefore, this study constructs a dialogue system that understands user values through conversation. Furthermore, the impact of understanding values on the interactions between dialogue systems and users is examined. The method is organized with a user model of preferences and values based on the established means-end chain model. We used a large language model (LLM) to estimate values based on the users’ preferences and the reasons they prefer them. Furthermore, an infinite relational model (IRM) estimates the relationships between multiple elements within the user model. The experiments show that the proposed method could estimate user values and enhance animacy and perceived intelligence in users’ impressions of an android robot, prompting new insights into users’ own values. The perception of the robot contributes to improved-quality interactions, and new insights into values facilitate a deeper self-understanding of users. This achievement, demonstrating the effects of using values for interaction, can provide valuable insights into human-robot interaction.
出版者	Springer Science and Business Media B.V.
収録物名	International Journal of Social Robotics
巻(号)	17
ページ	1003-1017
刊行年月	2025-05-15
言語	英語
ハンドルURL	https://hdl.handle.net/11094/102251
PISSN	18754791
eISSN	18754805
関連情報 (isIdenticalTo)	DOI (出版社版) https://doi.org/10.1007/s12369-025-01258-x
アクセス権	open access
権利情報	This article is licensed under a Creative Commons Attribution 4.0 International License.
出版タイプ	Version of Record
カテゴリ	学術雑誌論文 Journal Article

資源タイプ	学術雑誌論文
ローカル資源タイプ	学術雑誌論文
DCMI資源タイプ	text
DCTERMS.bibliographicCitation	International Journal of Social Robotics. 2025, 17, p. 1003-1017
DC.title	Effectiveness of Conversational Robots Capable of Estimating and Modeling User Values
DC.creator	Sakamoto, Yuki
	Uchida, Takahisa
	Ishiguro, Hiroshi
DC.publisher	Springer Science and Business Media B.V.
DC.language' scheme='DCTERMS.RFC1766	英語
DC.type' scheme='DCTERMS.DCMIType	text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2025-05-15
DC.identifier	https://doi.org/10.1007/s12369-025-01258-x
DC.subject	Conversational robot
	Human values
	Human-robot interaction (HRI)
	Personalization
DC.description	The version of record of this article, first published in International Journal of Social Robotics, is available online at Publisher’s website: https://doi.org/10.1007/s12369-025-01258-x.
DCTERMS.abstract	Personalizing a dialogue system according to the user has been recognized to have various positive effects. Despite the significance of user values, concepts guiding choices and evaluations being recognized in communication, they have not been considered in personalized dialogue systems. Therefore, this study constructs a dialogue system that understands user values through conversation. Furthermore, the impact of understanding values on the interactions between dialogue systems and users is examined. The method is organized with a user model of preferences and values based on the established means-end chain model. We used a large language model (LLM) to estimate values based on the users’ preferences and the reasons they prefer them. Furthermore, an infinite relational model (IRM) estimates the relationships between multiple elements within the user model. The experiments show that the proposed method could estimate user values and enhance animacy and perceived intelligence in users’ impressions of an android robot, prompting new insights into users’ own values. The perception of the robot contributes to improved-quality interactions, and new insights into values facilitate a deeper self-understanding of users. This achievement, demonstrating the effects of using values for interaction, can provide valuable insights into human-robot interaction.
DC.rights	This article is licensed under a Creative Commons Attribution 4.0 International License.
DC.format	102251
citation_title	Effectiveness of Conversational Robots Capable of Estimating and Modeling User Values
citation_author	Sakamoto, Yuki
	Uchida, Takahisa
	Ishiguro, Hiroshi
citation_publisher	Springer Science and Business Media B.V.
citation_language	英語
citation_date	2025-05-15
citation_journal_title	International Journal of Social Robotics
citation_volume	17
citation_firstpage	1003
citation_lastpage	1017
citation_doi	https://doi.org/10.1007/s12369-025-01258-x
citation_public_url	https://hdl.handle.net/11094/102251

Effectiveness of Conversational Robots Capable of Estimating and Modeling User Values

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