How Do You Like Me in This: User Embodiment Preferences for Companion Agents

We investigate the relationship between the embodiment of an artificial companion and user perception and interaction with it. In a Wizard of Oz study, 42 users interacted with one of two embodiments: a physical robot or a virtual agent on a screen through a role-play of secretarial tasks in an office, with the companion providing essential assistance. Findings showed that participants in both condition groups when given the choice would prefer to interact with the robot companion, mainly for its greater physical or social presence. Subjects also found the robot less annoying and talked to it more naturally. However, this preference for the robotic embodiment is not reflected in the users’ actual rating of the companion or their interaction with it. We reflect on this contradiction and conclude that in a task-based context a user focuses much more on a companion’s behaviour than its embodiment. This underlines the feasibility of our efforts in creating companions that migrate between embodiments while maintaining a consistent identity from the user’s point of view

Agent mediation and management of virtual communities: a redefinition of the traditional community concept

The paper explores the evolution of the concept of community in the light of computer mediated immersive virtual environments. The traditional concept of community has become strained in its attempts to capture the evolving virtual community. We believe the concept of the virtual community is of paramount importance and examine the extent to which this is being redefined to cater for it. We examine the management and mediation of such an environment and specifically the social process associated with the cohabited users. We advocate the use of multi-agent systems in delivering this functionalit

Investigating How Speech And Animation Realism Influence The Perceived Personality Of Virtual Characters And Agents

The portrayed personality of virtual characters and agents is understood to influence how we perceive and engage with digital applications. Understanding how the features of speech and animation drive portrayed personality allows us to intentionally design characters to be more personalized and engaging. In this study, we use performance capture data of unscripted conversations from a variety of actors to explore the perceptual outcomes associated with the modalities of speech and motion. Specifically, we contrast full performance-driven characters to those portrayed by generated gestures and synthesized speech, analysing how the features of each influence portrayed personality according to the Big Five personality traits. We find that processing speech and motion can have mixed effects on such traits, with our results highlighting motion as the dominant modality for portraying extraversion and speech as dominant for communicating agreeableness and emotional stability. Our results can support the Extended Reality (XR) community in development of virtual characters, social agents and 3D User Interface (3DUI) agents portraying a range of targeted personalities

First impressions: users’ judgments of virtual agents’ personality and interpersonal attitude in first encounters

In first encounters people quickly form impressions of each other’s personality and interpersonal attitude. We conducted a study to investigate how this transfers to first encounters between humans and virtual agents. In the study, subjects’ avatars approached greeting agents in a virtual museum rendered in both first and third person perspective. Each agent exclusively exhibited nonverbal immediacy cues (smile, gaze and proximity) during the approach. Afterwards subjects judged its personality (extraversion) and interpersonal attitude (hostility/friendliness). We found that within only 12.5 seconds of interaction subjects formed impressions of the agents based on observed behavior. In particular, proximity had impact on judgments of extraversion whereas smile and gaze on friendliness. These results held for the different camera perspectives. Insights on how the interpretations might change according to the user’s own personality are also provided

Virtual Meeting Rooms: From Observation to Simulation

Virtual meeting rooms are used for simulation of real meeting behavior and can show how people behave, how they gesture, move their heads, bodies, their gaze behavior during conversations. They are used for visualising models of meeting behavior, and they can be used for the evaluation of these models. They are also used to show the effects of controlling certain parameters on the behavior and in experiments to see what the effect is on communication when various channels of information - speech, gaze, gesture, posture - are switched off or manipulated in other ways. The paper presents the various stages in the development of a virtual meeting room as well and illustrates its uses by presenting some results of experiments to see whether human judges can induce conversational roles in a virtual meeting situation when they only see the head movements of participants in the meeting

Designing Sound for Social Robots: Advancing Professional Practice through Design Principles

Sound is one of the core modalities social robots can use to communicate with the humans around them in rich, engaging, and effective ways. While a robot's auditory communication happens predominantly through speech, a growing body of work demonstrates the various ways non-verbal robot sound can affect humans, and researchers have begun to formulate design recommendations that encourage using the medium to its full potential. However, formal strategies for successful robot sound design have so far not emerged, current frameworks and principles are largely untested and no effort has been made to survey creative robot sound design practice. In this dissertation, I combine creative practice, expert interviews, and human-robot interaction studies to advance our understanding of how designers can best ideate, create, and implement robot sound. In a first step, I map out a design space that combines established sound design frameworks with insights from interviews with robot sound design experts. I then systematically traverse this space across three robot sound design explorations, investigating (i) the effect of artificial movement sound on how robots are perceived, (ii) the benefits of applying compositional theory to robot sound design, and (iii) the role and potential of spatially distributed robot sound. Finally, I implement the designs from prior chapters into humanoid robot Diamandini, and deploy it as a case study. Based on a synthesis of the data collection and design practice conducted across the thesis, I argue that the creation of robot sound is best guided by four design perspectives: fiction (sound as a means to convey a narrative), composition (sound as its own separate listening experience), plasticity (sound as something that can vary and adapt over time), and space (spatial distribution of sound as a separate communication channel). The conclusion of the thesis presents these four perspectives and proposes eleven design principles across them which are supported by detailed examples. This work contributes an extensive body of design principles, process models, and techniques providing researchers and designers with new tools to enrich the way robots communicate with humans

Virtual Meeting Rooms: From Observation to Simulation

Much working time is spent in meetings and, as a consequence, meetings have become the subject of multidisciplinary research. Virtual Meeting Rooms (VMRs) are 3D virtual replicas of meeting rooms, where various modalities such as speech, gaze, distance, gestures and facial expressions can be controlled. This allows VMRs to be used to improve remote meeting participation, to visualize multimedia data and as an instrument for research into social interaction in meetings. This paper describes how these three uses can be realized in a VMR. We describe the process from observation through annotation to simulation and a model that describes the relations between the annotated features of verbal and non-verbal conversational behavior.\ud As an example of social perception research in the VMR, we describe an experiment to assess human observers’ accuracy for head orientation

Match or Mismatch? How Matching Personality and Gender between Voice Assistants and Users Affects Trust in Voice Commerce

Despite the ubiquity of voice assistants (VAs), they see limited adoption in the form of voice commerce, an online sales channel using natural language. A key barrier to the widespread use of voice commerce is the lack of user trust. To address this problem, we draw on similarity-attraction theory to investigate how trust is affected when VAs match the user’s personality and gender. We conducted a scenario-based experiment (N = 380) with four VAs designed to have different personalities and genders by customizing only the auditory cues in their voices. The results indicate that a personality match increases trust, while the effect of a gender match on trust is non-significant. Our findings contribute to research by demonstrating that some types of matches between VAs and users are more effective than others. Moreover, we reveal that it is important for practitioners to consider auditory cues when designing VAs for voice commerce