A User Study of a Humanoid Robot as a Social Mediator for Two-Person Conversations

Tahir, Yasir; Dauwels, Justin; Thalmann, Daniel; Thalmann, Nadia Magnenat

doi:10.1007/s12369-018-0478-3

Cited by 15 publications

(8 citation statements)

References 34 publications

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“…Based on the above discussion, an increasing number of applications, that use body movement information for emotion recognition, has emerged. One of the recent works used a robot as a social mediator to increase the quality of human-robot interaction [7]. Emotion recognition from body movement encompass a large number of applications including biometric security, healthcare, gaming, and behavior modeling [5].…”

Section: Development Of a Computer System Capable Of Predicting Emotimentioning

confidence: 99%

“…C Medical Rehabilitation. A Within the field of humanoid robots, as well as the general area of human-computer interaction, the need to understand and to imitate the behavior of a human is paramount [7], [30], [51], [52]. Some of the practical applications are enterprise greeting robots (at hotel receptions, university research centers, shopping centers), special needs robots, senior assistant robots, interaction with hearing impaired population, etc.…”

Section: Open Problemsmentioning

confidence: 99%

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Emotion Recognition From Body Movement

2020

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Automatic emotion recognition from the analysis of body movement has tremendous potential to revolutionize virtual reality, robotics, behavior modeling, and biometric identity recognition domains. A computer system capable of recognizing human emotion from the body can also significantly change the way we interact with the computers. One of the significant challenges is to identify emotion-specific features from a vast number of descriptors of human body movements. In this paper, we introduce a novel two-layer feature selection framework for emotion classification from a comprehensive list of body movement features. We used the feature selection framework to accurately recognize five basic emotions: happiness, sadness, fear, anger, and neutral. In the first layer, a unique combination of Analysis of Variance (ANOVA) and Multivariate Analysis of Variance (MANOVA) was utilized to eliminate irrelevant features. In the second layer, a binary chromosome-based genetic algorithm was proposed to select a feature subset from the relevant list of features that maximizes the emotion recognition rate. Score and rank-level fusion were applied to further improve the accuracy of the system. The proposed system was validated on proprietary and public datasets, containing 30 subjects. Different action scenarios, such as walking and sitting actions, as well as an action-independent case, were considered. Based on the experimental results, the proposed emotion recognition system achieved a very high emotion recognition rate outperforming all of the state-of-theart methods. The proposed system achieved recognition accuracy of 90.0% during walking, 96.0% during sitting, and 86.66% in an action-independent scenario, demonstrating high accuracy and robustness of the developed method.

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Section: Development Of a Computer System Capable Of Predicting Emotimentioning

confidence: 99%

Section: Open Problemsmentioning

confidence: 99%

Emotion Recognition From Body Movement

2020

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“…For remote communication support, telepresence robots have been used as mediators of interpersonal communication, and the applicability was tested for elderly support (e.g., health care [8,30], working support [23,44]). Furthermore, social mediator robots that support local interpersonal communication were also proposed [47,51,54]. These studies suggest that through interaction with mediator robots, humans may be encouraged to communicate with other people (e.g., elderly people are motivated to interact with caregivers during their interaction with a Paro robot [51]).…”

Section: Robot-mediated Communicationmentioning

confidence: 99%

“…Although more improvements are needed, they are particularly welcomed by users who feel stress in key typing. Most importantly, if social robots mediate interpersonal communication [51,54] in an appropriate manner, self-disclosure of elderly people could be encouraged-for instance, it may become easier for elderly people to self-disclose in this way than directly talking over the phone. However, the concept of the social mediator robot, particularly in the context of encouraging elderly self-disclosure, is still unexplored, and little knowledge is available with respect to the design guidelines.…”

Section: Introductionmentioning

confidence: 99%

Personality Traits for a Social Mediator Robot Encouraging Elderly Self-Disclosure on Loss Experiences

Noguchi

Kamide

Tanaka

2020

J. Hum.-Robot Interact.

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To prevent elderly people from being socially isolated, encouraging their self-disclosure takes an important role. We discuss a use case of social robots in which they are deployed as mediators for humans that intermediate remote communication between elderly people and their family members or friends. The goal of this article is to present a design guideline for such social mediator robots based on results obtained from two studies in which a total of 741 elderly people participated. In study 1, we explored topics in dialogues and found that a social mediator robot could well encourage the self-disclosure of the elderly people, particularly in topics of which they usually feel resistance in talking to others (e.g., loss experiences). Thus, we confirmed the feasibility of the social mediator robot. Study 2 pursued the effective personality traits of the social mediator robot. We re-investigated a well-studied research question of matching robot personality to the user. The results provided more detailed knowledge as to similarity-attraction/repulsion than had been reported previously. Finally, design recommendations were discussed by considering the personality traits of the elderly users as well. CCS Concepts: • Computer systems organization → Robotics; • Human-centered computing → Interaction design; User studies;

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“…1) Studies in Mediating Conversation: This work follows prior work in which the robot acted as both a mediator and facilitator in order to improve the quality and balance of a conversation. Tahir et al [18] focused on different methods for improving conversational quality using a robot mediator to deliver feedback about a conversation between two individuals. In that study, two individuals acted out a scripted conversation and then the robot delivers feedback created by a 'sociofeedback system' which analyzed the interest, dominance, and agreement displayed in the conversation.…”

Section: A Multi-party Human-robot Interactionmentioning

confidence: 99%

Can I Trust You? A User Study of Robot Mediation of a Support Group

Birmingham¹,

Hu²,

Mahajan³

et al. 2020

Preprint

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Socially assistive robots have the potential to improve group dynamics when interacting with groups of people in social settings. This work contributes to the understanding of those dynamics through a user study of trust dynamics in the novel context of a robot mediated support group. For this study, a novel framework for robot mediation of a support group was developed and validated. To evaluate interpersonal trust in the multi-party setting, a dyadic trust scale was implemented and found to be uni-factorial, validating it as an appropriate measure of general trust. The results of this study demonstrate a significant increase in average interpersonal trust after the group interaction session, and qualitative post-session interview data report that participants found the interaction helpful and successfully supported and learned from one other. The results of the study validate that a robot-mediated support group can improve trust among strangers and allow them to share and receive support for their academic stress.

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A User Study of a Humanoid Robot as a Social Mediator for Two-Person Conversations

Abstract: A user study of a humanoid robot as a social mediator for two-person conversations

Cited by 15 publications

References 34 publications

Emotion Recognition From Body Movement

Emotion Recognition From Body Movement

Personality Traits for a Social Mediator Robot Encouraging Elderly Self-Disclosure on Loss Experiences

Can I Trust You? A User Study of Robot Mediation of a Support Group

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