User profiling and behavioral adaptation for HRI: A survey

Rossi, Silvia; Ferland, Franois; Tapus, Adriana

doi:10.1016/j.patrec.2017.06.002

Cited by 140 publications

(51 citation statements)

References 49 publications

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“…user name, gender, personality) and dynamic (e.g. emotion, current response) parameters [16], [17]. In socially assistive robotic systems, personalization should be considered from therapeutic aspects (e.g.…”

Section: B Personalized Robot Behaviorsmentioning

confidence: 99%

A Personalized and Platform-Independent Behavior Control System for Social Robots in Therapy: Development and Applications

Cao,

Van de Perre,

Kennedy

et al. 2019

IEEE Trans. Cogn. Dev. Syst.

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Social robots have been proven beneficial in different types of healthcare interventions. An ongoing trend is to develop (semi-)autonomous socially assistive robotic systems in healthcare context to improve the level of autonomy and reduce human workload. This paper presents a behavior control system for social robots in therapies with a focus on personalization and platform-independence. This system architecture provides the robot an ability to behave as a personable character, which behaviors are adapted to user profiles and responses during the human-robot interaction. Robot behaviors are designed at abstract levels and can be transferred to different social robot platforms. We adopt the component-based software engineering approach to implement our proposed architecture to allow for the replaceability and reusability of the developed components. We introduce three different experimental scenarios to validate the usability of our system. Results show that the system is potentially applicable to different therapies and social robots. With the component-based approach, the system can serve as a basic framework for researchers to customize and expand the system for their targeted healthcare applications.

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Section: B Personalized Robot Behaviorsmentioning

confidence: 99%

A Personalized and Platform-Independent Behavior Control System for Social Robots in Therapy: Development and Applications

Cao,

Van de Perre,

Kennedy

et al. 2019

IEEE Trans. Cogn. Dev. Syst.

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“…Different from affective recognition problems, empathy relies mostly on contextual, personalized and continuous interactions. By bonding with one specific person over time, we can develop a specific empathetic response towards that person [10].…”

Section: Introductionmentioning

confidence: 99%

The OMG-Empathy Dataset: Evaluating the Impact of Affective Behavior in Storytelling

Barros

Churamani

Lim

et al. 2019

2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)

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Processing human affective behavior is important for developing intelligent agents that interact with humans in complex interaction scenarios. A large number of current approaches that address this problem focus on classifying emotion expressions by grouping them into known categories. Such strategies neglect, among other aspects, the impact of the affective responses from an individual on their interaction partner thus ignoring how people empathize towards each other. This is also reflected in the datasets used to train models for affective processing tasks. Most of the recent datasets, in particular, the ones which capture natural interactions ("in-the-wild" datasets), are designed, collected, and annotated based on the recognition of displayed affective reactions, ignoring how these displayed or expressed emotions are perceived. In this paper, we propose a novel dataset composed of dyadic interactions designed, collected and annotated with a focus on measuring the affective impact that eight different stories have on the listener. Each video of the dataset contains around 5 minutes of interaction where a speaker tells a story to a listener. After each interaction, the listener annotated, using a valence scale, how the story impacted their affective state, reflecting how they empathized with the speaker as well as the story. We also propose different evaluation protocols and a baseline that encourages participation in the advancement of the field of artificial empathy and emotion contagion.

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“…For example, Teixeira C, Pinto J S, Martins J A provide a new approach about how user modelling applications can be integrated into any organization without the cost of reengineering the entire information system already in place [3]. Silvia Rossi, François Ferland, Adriana Tapus find that the current literature introduces a general classification scheme for both the profiling and the behavioral adaptation research topics in terms of physical, cognitive, and social interaction viewpoints [4].…”

Section: Introductionmentioning

confidence: 99%

Research on the Annual Reading Report of Academic Libraries Based on Personas

Lan¹,

Wang²

2018

JSS

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This paper expounds relevant theoretical research on personas and the advantages of the annual reading report of academic college library based on personas, and expounds the construction of personas in detail from four aspects: data collection, behavior modeling, construction personas and visual presentation. The annual reading report of the academic college library with personas digs in depth all kinds of reading data in the library, constructs personas model by using a set of tags, objectively understands the reader's reading tendency, and facilitates librarians to carry out accurate reading promotion services.

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User profiling and behavioral adaptation for HRI: A survey

Cited by 140 publications

References 49 publications

A Personalized and Platform-Independent Behavior Control System for Social Robots in Therapy: Development and Applications

A Personalized and Platform-Independent Behavior Control System for Social Robots in Therapy: Development and Applications

The OMG-Empathy Dataset: Evaluating the Impact of Affective Behavior in Storytelling

Research on the Annual Reading Report of Academic Libraries Based on Personas

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