Eliciting Cooperative Persuasive Dialogue by Multimodal Emotional Robot

Asai, Sara; Yoshino, Katsumi; Shinagawa, Seitaro; Sakti, Sakriani; Nakamura, Satoshi

doi:10.1007/978-981-19-5538-9_10

Cited by 5 publications

(8 citation statements)

References 21 publications

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“…We solely manipulated the robot's verbal communication style which did not affect the acceptance of the robot. This result is in contrast to previous studies, where the manipulation of several robot interaction features (e.g., eye color, gaze behavior, and gestures) including verbal communication produced higher compliance (Maggi et al, 2021;Maggi et al, 2020) higher persuasion (Asai et al, 2022;Saunderson and Nejat, 2022;Saunderson and Nejat, 2019), or higher cooperation in a moral dilemma (Takahashi et al, 2021). Verbal communication alone seems to have little effect on the acceptance of a robot as an advisor in moral decision-making.…”

Section: Acceptance Of Robots As Advisors In Moral Decision-makingcontrasting

confidence: 99%

“…Links between emotions and persuasiveness are not only known from human-human communication (Rocklage et al, 2018) but also found in human-robot interaction (Green and Works, 2022;Asai et al, 2022;Saunderson and Nejat, 2022;Saunderson and Nejat, 2019). In the prisoner's dilemma, subjects were more likely to cooperate with a robot when the robot showed emotion (Takahashi et al, 2021).…”

Section: The Impact Of Social Communicationmentioning

confidence: 99%

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Increased morality through social communication or decision situation worsens the acceptance of robo-advisors

Arlinghaus,

Strassmann,

Dix

2024

Preprint

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This German study (N = 317) tests social communication (i.e., self-disclosure, content intimacy, relational continuity units, we-phrases) as a potential compensation strategy for algorithm aversion. Therefore, we explore the acceptance of a robot as an advisor in non-moral, somewhat moral, and very moral decision situations and compare the influence of two verbal communication styles of the robot (functional vs. social). Subjects followed the robot’s recommendation similarly often for both communication styles (functional vs. social), but more often in the non-moral decision situation than in the moral decision situations. Subjects perceived the robot as more human and more moral during social communication than during functional communication but similarly trustworthy, likable, and intelligent for both communication styles. In moral decision situations, subjects ascribed more anthropomorphism and morality but less trust, likability, and intelligence to the robot compared to the non-moral decision situation. Subjects perceive the robot as more moral in social communication. This unexpectedly led to subjects following the robot’s recommendation less often. No other mediation effects were found. From this we conclude, that the verbal communication style alone has a rather small influence on the robot’s acceptance as an advisor for moral decision-making and does not reduce algorithm aversion. Potential reasons for this (e.g., multimodality, no visual changes), as well as implications (e.g., avoidance of self-disclosure in human-robot interaction) and limitations (e.g., video interaction) of this study, are discussed.

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Section: Acceptance Of Robots As Advisors In Moral Decision-makingcontrasting

confidence: 99%

Section: The Impact Of Social Communicationmentioning

confidence: 99%

Increased morality through social communication or decision situation worsens the acceptance of robo-advisors

Arlinghaus,

Strassmann,

Dix

2024

Preprint

View full text Add to dashboard Cite

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“…The approach of Suguitan et al [ 19 ] uses a variational autoencoder and an emotion classifier for modulating neutral expressions into affective expressions. Asai et al [ 41 ] also proposed adapting the robot’s responses to its emotional state. The system first uses BERT to select the predefined answer that better works as a response to the user’s utterance.…”

Section: Related Workmentioning

confidence: 99%

“…This is the case for the works of Hasegawa et al [ 21 ], Ravenet et al [ 27 ], Kucherenko et al [ 22 ], Ginosar et al [ 23 ], Yoon et al [ 24 ], Yoon et al [ 43 ], Spitale and Matarić [ 28 ], Ahuja et al [ 33 ], Fares et al [ 34 ], and Qi et al [ 30 ]. Among the works that use handcrafted expressions, there are also several authors that focused exclusively on the combination of speech and body motions and posture, like Meena et al [ 35 ], Xu et al [ 18 ], or Asai et al [ 41 ]. There are also authors that only considered body motions and postures, without the verbal component.…”

Section: Related Workmentioning

confidence: 99%

“…The proposed system then selects between both sources of emotions based on a priority system and executes the emotional expressions associated with each source. The approach of Asai et al [ 41 ] updated the robot’s emotional state using a logistic regression model that takes the previous state and the dialogue history. Their system not only considers different emotional expressions, but also emotional versions of the robot’s utterances.…”

Section: Related Workmentioning

confidence: 99%

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Creating Expressive Social Robots That Convey Symbolic and Spontaneous Communication

Fernández-Rodicio,

Castro-González,

Gamboa-Montero

et al. 2024

Sensors

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Robots are becoming an increasingly important part of our society and have started to be used in tasks that require communicating with humans. Communication can be decoupled in two dimensions: symbolic (information aimed to achieve a particular goal) and spontaneous (displaying the speaker’s emotional and motivational state) communication. Thus, to enhance human–robot interactions, the expressions that are used have to convey both dimensions. This paper presents a method for modelling a robot’s expressiveness as a combination of these two dimensions, where each of them can be generated independently. This is the first contribution of our work. The second contribution is the development of an expressiveness architecture that uses predefined multimodal expressions to convey the symbolic dimension and integrates a series of modulation strategies for conveying the robot’s mood and emotions. In order to validate the performance of the proposed architecture, the last contribution is a series of experiments that aim to study the effect that the addition of the spontaneous dimension of communication and its fusion with the symbolic dimension has on how people perceive a social robot. Our results show that the modulation strategies improve the users’ perception and can convey a recognizable affective state.

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Effects of Demonstrating Consensus Between Robots to Change User’s Opinion

Sakai,

Mitsuda,

Yoshikawa

et al. 2024

Int J of Soc Robotics

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In recent years, the research of humanoid robots that can change users’ opinions has been conducted extensively. In particular, two robots have been found to be able to improve their persuasiveness by cooperating with each other in a sophisticated manner. Previous studies have evaluated the changes in opinions when robots showed consensus building. However, users did not participate in the conversations, and the optimal strategy may change depending on their prior opinions. Therefore, in this study, we developed a system that adaptively changes conversations between robots based on user opinions. We investigate the effect on the change in opinions when the discussion converges to the same position as the user and when it converges to a different position. We conducted two subject experiments in which a user and virtual robotic agents talked to each other using buttons in a crowded setting. The results showed that users with confidence in their opinions increased their confidence when the robot agents’ opinions converged to the same position and decreased their confidence when the robot agents’ opinions converged to a different position. This will significantly contribute to persuasion research using multiple robots and the development of advanced dialogue coordination between robots.

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Eliciting Cooperative Persuasive Dialogue by Multimodal Emotional Robot

Cited by 5 publications

References 21 publications

Increased morality through social communication or decision situation worsens the acceptance of robo-advisors

Increased morality through social communication or decision situation worsens the acceptance of robo-advisors

Creating Expressive Social Robots That Convey Symbolic and Spontaneous Communication

Effects of Demonstrating Consensus Between Robots to Change User’s Opinion

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