A Systematic Survey of 15 Years of User Studies Published in the Intelligent Virtual Agents Conference

Norouzi, Nahal; Kim, Kangsoo; Hochreiter, Jason; Lee, Myungho; Daher, Salam; Bruder, Gerd; Welch, Greg

doi:10.1145/3267851.3267901

Cited by 50 publications

(13 citation statements)

References 92 publications

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“…For instance, a number of studies in the field of multimodal human-computer interaction show that people not only perceive ECA behavior in a certain way, but also adapt to it in real-time [Norouzi et al, 2018;Zhang at al., 2010;Bohus, Horvitz, 2010]. If the agent is set up to track an object at the center of the user's attention 90 % of the time, the user will pay less attention to the virtual agent.…”

Section: Towards a Multimodal Framework In Hci Researchmentioning

confidence: 99%

The Rise of Interactional Multimodality in Human-Computer Interaction

Klowait

Erofeeva

2021

MONITORING OF PUBLIC OPINION

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The field of human-computer interaction (HCI) investigates the intersection between the design of devices and users. From an early focus on interaction modeling based on psychological experiments, the field has since experienced a shift towards the study of how actual humans interact with autonomous devices. The field became conductive to ethnographic, observational and videographic studies of human-device interaction. Conversation-analytic HCI became possible. That said, this new wave of researchers was never truly able to dethrone the psychological common sense of the field. With recent developments in both the technical-sensorial capabilities and outward actuational range of embodied virtual agents, the field of HCI has once again returned to the question of the sequential unfolding of the interaction between users and intelligent agents, and the multimodal interactional repertoire that is deployed throughout. This review will highlight the situational orientation of high-impact research in the field, and relate it to the cotemporaneous development of ethnomethodological and conversation analytic frameworks. Acknowledgments. The article was prepared in the framework of a research grant funded by the Ministry of Science and Higher Education of the Russian Federation (grant ID: 075-15-2020-908). The article was prepared in cooperation with the Sber (ex. – Sberbank’s) Gamification Lab.

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Section: Towards a Multimodal Framework In Hci Researchmentioning

confidence: 99%

The Rise of Interactional Multimodality in Human-Computer Interaction

Klowait

Erofeeva

2021

MONITORING OF PUBLIC OPINION

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“…Beyond collaborations between human users, there is increasing research in human-machine (or humanagent) collaborations, considering the convergence of advanced artificial intelligence (AI), such as intelligent virtual assistants, and immersive AR/VR technologies [39]. This paper Zhou et al [48] explores the effect of a user's personality trait on the level of trust in a machine's decisions when collaborating with the machine.…”

Section: Effects Of Personality Traits On User Trust In Human-machine Collaborationsmentioning

confidence: 99%

Multimodal interfaces and communication cues for remote collaboration

Kim

Billinghurst

Kim

2020

J Multimodal User Interfaces

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Remote collaboration has been studied for more than two decades and now there is the possibilities for new types of collaboration with the recent advances in immersive technologies such as Virtual, Augmented, Mixed Reality (VR/AR/MR). However, despite the increasing research interest in remote collaboration study with VR/AR/MR technologies, there is still a lack of academic venues specifically focusing on VR/AR/MR remote collaboration research. This special issue provides high-quality papers on the topic of remote collaboration research and increases visibility of this timely interesting and important research area. We particularly focus on three research aspects in remote collaboration: (1) use of multimodal communication cues, (2) awareness of the task space, and (3) human factors understanding. In this editorial, we first describe five essential factors for remote collaboration: task, local user, remote user, communication, and tool/interface, and then summarize a brief history of the research areas. We also cover the feature papers accepted in this issue, which introduce novel multimodal interfaces for remote collaboration and the effects on task performance and perceptual factors. Finally, we discuss some potential future research directions while concluding the editorial.

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“…Significant research has focused on IVAs and their appearance, behaviors, and movements [45]. Norouzi et al [50] surveyed previous work on speech modeling, verbal and non-verbal behavior, physical appearance, and identities of IVAs. Verbal approaches have been used to model different characteristics of speech and dialogues (e.g., emotions [24]).…”

Section: Intelligent Virtual Agent Modelingmentioning

confidence: 99%

FVA:Modeling Perceived Friendliness of Virtual Agents Using Movement Characteristics

Randhavane

Bera

Kapsaskis

et al. 2019

IEEE Trans. Visual. Comput. Graphics

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Figure 1: Friendly Virtual Agent (FVA) : We present an algorithm to model perceived friendliness of a virtual agent by varying its gaze (A), gait (B), and gestures corresponding to head nodding (C) and waving (D). These movement cues are generated using our novel data-driven friendliness model. We evaluate the benefits in terms of an improved sense of social presence using an AR validation study using a HoloLens. ABSTRACTWe present a new approach for improving the friendliness and warmth of a virtual agent in an AR environment by generating appropriate movement characteristics. Our algorithm is based on a novel data-driven friendliness model that is computed using a userstudy and psychological characteristics. We use our model to control the movements corresponding to the gaits, gestures, and gazing of friendly virtual agents (FVAs) as they interact with the user's avatar and other agents in the environment. We have integrated FVA agents with an AR environment using with a Microsoft HoloLens. Our algorithm can generate plausible movements at interactive rates to increase the social presence. We also investigate the perception of * a user in an AR setting and observe that an FVA has a statistically significant improvement in terms of the perceived friendliness and social presence of a user compared to an agent without the friendliness modeling. We observe an increment of 5.71% in the mean responses to a friendliness measure and an improvement of 4.03% in the mean responses to a social presence measure.

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A Systematic Survey of 15 Years of User Studies Published in the Intelligent Virtual Agents Conference

Cited by 50 publications

References 92 publications

The Rise of Interactional Multimodality in Human-Computer Interaction

The Rise of Interactional Multimodality in Human-Computer Interaction

Multimodal interfaces and communication cues for remote collaboration

FVA:Modeling Perceived Friendliness of Virtual Agents Using Movement Characteristics

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