Formalizing Joint Attention in Cooperative Interaction with a Virtual Human

Pfeiffer-Leßmann, Nadine; Wachsmuth, Ipke

doi:10.1007/978-3-642-04617-9_68

Cited by 6 publications

(4 citation statements)

References 11 publications

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“…Hoffmann et al (2009) state that this sense of social presence frequently leads participants to interact with virtual guides, similarly to how they engage with real humans, which is consistent with the Media Equation theory (Reeves and Nass, 1996;Hoffmann et al, 2009). To further enhance the social presence, it is, moreover, crucial for virtual guides to align their behavior with user expectations (Ibáñez-Martínez et al, 2008), incorporating factors such as gazing (Martinez et al, 2010;Pfeiffer-Lessmann et al, 2012;Pejsa et al, 2015) and gestures (Jerald, 2015). Additionally, natural user-agent interaction can be enhanced by including linguistic style adjustments as found in research by, e.g., de Jong et al (2008) in terms of politeness and formality, or by Ibanez et al (2003a) and Ibanez et al (2003b) in terms of the audience and the VA's background and character.…”

Section: Characteristicmentioning

confidence: 61%

Wayfinding in immersive virtual environments as social activity supported by virtual agents

Bönsch,

Ehret,

Rupp

et al. 2024

Front. Virtual Real.

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Effective navigation and interaction within immersive virtual environments (IVEs) rely on thorough scene exploration. Therefore, wayfinding is essential, assisting users in comprehending their surroundings, planning routes, and making informed decisions. Based on real-life observations, wayfinding is, thereby, not only a cognitive process but also a social activity profoundly influenced by the presence and behaviors of others. In virtual environments, these “others” are virtual agents (VAs), defined as anthropomorphic computer-controlled characters, who enliven the environment and can serve as background characters or direct interaction partners. However, less research has been conducted to explore how to efficiently use VAs as social wayfinding support. In this paper, we aim to assess and contrast user experience, user comfort, and acquisition of scene knowledge through a between-subjects study involving n = 60 participants across three distinct wayfinding conditions in one slightly populated urban environment: (i) unsupported wayfinding, (ii) strong social wayfinding using a virtual supporter who incorporates guiding and accompanying elements while directly impacting the participants’ wayfinding decisions, and (iii) weak social wayfinding using flows of VAs that subtly influence the participants’ wayfinding decisions by their locomotion behavior. Our work is the first to compare the impact of VAs’ behavior in virtual reality on users’ scene exploration, including spatial awareness, scene comprehension, and comfort. The results show the general utility of social wayfinding support, while underscoring the superiority of the strong type. Nevertheless, further exploration of weak social wayfinding as a promising technique is needed. Thus, our work contributes to the enhancement of VAs as advanced user interfaces, increasing user acceptance and usability.

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Section: Characteristicmentioning

confidence: 61%

Wayfinding in immersive virtual environments as social activity supported by virtual agents

Bönsch,

Ehret,

Rupp

et al. 2024

Front. Virtual Real.

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“…In this respect, the present framework could be a valuable tool to define respective JA situations, their affordances, and determine the respective probabilistic and temporal parameters during real-life human-agent interaction. This is an essential step for the construction of realistic artificial agents for any kind of system for human interaction (e.g., Pfeiffer-Leßmann and Wachsmuth, 2009;Yu et al, 2010Yu et al, , 2012Grynszpan et al, 2012;Stephenson et al, 2018;Willemse et al, 2018).…”

Section: Naturalistic Human-agent Interactionmentioning

confidence: 99%

Temporal Behavioral Parameters of On-Going Gaze Encounters in a Virtual Environment

et al. 2021

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To navigate the social world, humans heavily rely on gaze for non-verbal communication as it conveys information in a highly dynamic and complex, yet concise manner: For instance, humans utilize gaze effortlessly to direct and infer the attention of a possible interaction partner. Many traditional paradigms in social gaze research though rely on static ways of assessing gaze interaction, e.g., by using images or prerecorded videos as stimulus material. Emerging gaze contingent paradigms, in which algorithmically controlled virtual characters can respond flexibly to the gaze behavior of humans, provide high ecological validity. Ideally, these are based on models of human behavior which allow for precise, parameterized characterization of behavior, and should include variable interactive settings and different communicative states of the interacting agents. The present study provides a complete definition and empirical description of a behavioral parameter space of human gaze behavior in extended gaze encounters. To this end, we (i) modeled a shared 2D virtual environment on a computer screen in which a human could interact via gaze with an agent and simultaneously presented objects to create instances of joint attention and (ii) determined quantitatively the free model parameters (temporal and probabilistic) of behavior within this environment to provide a first complete, detailed description of the behavioral parameter space governing joint attention. This knowledge is essential to enable the modeling of interacting agents with a high degree of ecological validity, be it for cognitive studies or applications in human-robot interaction.

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“…He makes use of information about a human's gaze and pointing gestures to assess their focus of attention. In doing so, Max is able to establish joint attention with the human communicative partner, and increase fluidity of the interaction (see Pfeiffer--Leßmann, & Wachsmuth, 2009;Wachsmuth, 2008). Information about the human partner's attention, in combination with emotion simulation, intention recognition, and the ability to give feedback in conversation (Becker--Asano & Wachsmuth, 2010;Wachsmuth, 2008), make the experience of interacting with Max seem virtually real.…”

Section: Gazementioning

confidence: 99%

Visual environment and interlocutors in situated dialogue

Brown‐Schmidt¹

2016

Advances in Consciousness Research

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Face-to-face conversation is often considered the most basic form of language use, as it was likely a dominant mode of communication as languages evolved, it is often the primary form of language input during children's language acquisition, and it is a dominant mode of adult communication today. Conversational language differs in important ways from the language traditionally studied in psycholinguistics; thus, characterizing language processing in conversation is essential if models of language understanding are to extend to this most basic form of language use. This chapter will examine key features of language comprehension in conversation, and will highlight the role of the visual environment in establishing joint domains of reference. Unlike in non-interactive settings, in conversation language is jointly created by conversational partners who hold different, but partially overlapping representations of the relevant context. Understanding if and how partners appreciate their partner's perspective has emerged as a central question in this domain.

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Formalizing Joint Attention in Cooperative Interaction with a Virtual Human

Cited by 6 publications

References 11 publications

Wayfinding in immersive virtual environments as social activity supported by virtual agents

Wayfinding in immersive virtual environments as social activity supported by virtual agents

Temporal Behavioral Parameters of On-Going Gaze Encounters in a Virtual Environment

Visual environment and interlocutors in situated dialogue

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