Virtual Reality as a Tool for Studying Diversity and Inclusion in Human-Robot Interaction: Advantages and Challenges

This paper investigates the potential of Virtual Reality (VR) as a research tool for studying diversity and inclusion characteristics in the context of human-robot interactions (HRI). Some exclusive advantages of using VR in HRI are discussed, such as a controllable environment, the possibility to manipulate the variables related to the robot and the human-robot interaction, flexibility in the design of the robot and the environment, and advanced measurement methods related e.g. to eye tracking and physiological data. At the same time, the challenges of researching diversity and inclusion in HRI are described, especially in accessibility, cyber sickness and bias when developing VR-environments. Furthermore, solutions to these challenges are being discussed to fully harness the benefits of VR for the studying of diversity and inclusion.Comment: 4 page

Age-related differences in the evaluation of a virtual health agent’s appearance and embodiment in a health-related interaction: Experimental lab study

Straßmann C, Krämer NC, Buschmeier H, Kopp S. Age-related differences in the evaluation of a virtual health agent’s appearance and embodiment in a health-related interaction: Experimental lab study. Journal of Medical Internet Research. 2020;22(4): e13726.**Background:** Assistive technologies have become more important owing to the aging population, especially when they foster healthy behaviors. Because of their natural interface, virtual agents are promising assistants for people in need of support. To engage people during an interaction with these technologies, such assistants need to match the users´ needs and preferences, especially with regard to social outcomes. **Objective:** Prior research has already determined the importance of an agent’s appearance in a human-agent interaction. As seniors can particularly benefit from the use of virtual agents to maintain their autonomy, it is important to investigate their special needs. However, there are almost no studies focusing on age-related differences with regard to appearance effects. **Methods:** A 2×4 between-subjects design was used to investigate the age-related differences of appearance effects in a human-agent interaction. In this study, 46 seniors and 84 students interacted in a health scenario with a virtual agent, whose appearance varied (cartoon-stylized humanoid agent, cartoon-stylized machine-like agent, more realistic humanoid agent, and nonembodied agent [voice only]). After the interaction, participants reported on the evaluation of the agent, usage intention, perceived presence of the agent, bonding toward the agent, and overall evaluation of the interaction. **Results:** The findings suggested that seniors evaluated the agent more positively (liked the agent more and evaluated it as more realistic, attractive, and sociable) and showed more bonding toward the agent regardless of the appearance than did students. In addition, interaction effects were found. Seniors reported the highest usage intention for the cartoon-stylized humanoid agent, whereas students reported the lowest usage intention for this agent. The same pattern was found for participant bonding with the agent. Seniors showed more bonding when interacting with the cartoon-stylized humanoid agent or voice only agent, whereas students showed the least bonding when interacting with the cartoon-stylized humanoid agent. **Conclusions:** In health-related interactions, target group–related differences exist with regard to a virtual assistant’s appearance. When elderly individuals are the target group, a humanoid virtual assistant might trigger specific social responses and be evaluated more positively at least in short-term interactions

Linguistic alignment with artificial entities in the context of second languageacquisition

Native-speakers often adapt to non-natives in order to foster mutual understanding and successful communication,sometimes with the negative outcome of interfering with successful second language acquisition (SLA) on a native-speakerlevel. In two experimental studies we explored the potential of artificial tutors to avoid inhibition effects and exploit linguisticalignment processes in HCI for SLA. Study 1 (n=130 non-native speakers) investigated the influence of system voice (text-to-speech vs. pre-recorded speech) and embodiment (virtual agent vs. robot vs. speech based interaction) on participants’perception of the system, their motivation, their lexical and syntactical alignment during interaction and their learning effectafter the interaction, while in Study 2 (n=85) embodiment and the presence of expressive nonverbal behavior were varied. Thevariation of system characteristics had barely influence on the evaluation of the system or participants’ alignment behavior.Moreover, although participants linguistically aligned this did not result in significant short-term learning effects

A New Design Paradigm for Secure Full-Duplex Multiuser Systems

We consider a full-duplex (FD) multiuser system where an FD base station (BS) is designed to simultaneously serve both downlink (DL) and uplink (UL) users in the presence of half-duplex eavesdroppers (Eves). The problem is to maximize the minimum (max-min) secrecy rate (SR) among all legitimate users, where the information signals at the FD-BS are accompanied with artificial noise to debilitate the Eves' channels. To enhance the max-min SR, a major part of the power budget should be allocated to serve the users with poor channel qualities, such as those far from the FD-BS, undermining the SR for other users, and thus compromising the SR per-user. In addition, the main obstacle in designing an FD system is due to the self-interference (SI) and co-channel interference (CCI) among users. We therefore propose an alternative solution, where the FD-BS uses a fraction of the time block to serve near DL users and far UL users, and the remaining fractional time to serve other users. The proposed scheme mitigates the harmful effects of SI, CCI and multiuser interference, and provides system robustness. The SR optimization problem has a highly nonconcave and nonsmooth objective, subject to nonconvex constraints. For the case of perfect channel state information (CSI), we develop a low-complexity path-following algorithm, which involves only a simple convex program of moderate dimension at each iteration. We show that our path-following algorithm guarantees convergence at least to a local optimum. Then, we extend the path-following algorithm to the cases of partially known Eves' CSI, where only statistics of CSI for the Eves are known, and worst-case scenario in which Eves can employ a more advanced linear decoder. The merit of our proposed approach is further demonstrated by extensive numerical results.Comment: Accepted for publication in IEEE Journal on Selected Areas in Communications (JSAC), 201

Conversational Assistants for Elderly Users – The Importance of Socially Cooperative Dialogue

Kopp S, Brandt M, Buschmeier H, et al. Conversational Assistants for Elderly Users – The Importance of Socially Cooperative Dialogue. In: André E, Bickmore T, Vrochidis S, Wanner L, eds. Proceedings of the AAMAS Workshop on Intelligent Conversation Agents in Home and Geriatric Care Applications co-located with the Federated AI Meeting. CEUR Workshop Proceedings. Vol 2338. Aachen: RWTH; 2018: 10–17.Conversational agents can provide valuable cognitive and/or emotional assistance to elderly users or people with cognitive impairments who often have difficulties in organizing and following a structured day schedule. Previous research showed that a virtual assistant that can interact in spoken language would be a desirable help for those users. However, these user groups pose specific requirements for spoken dialogue interaction that existing systems hardly meet. This paper presents work on a virtual conversational assistant that was designed for, and together with, elderly as well as cognitively handicapped users. It has been specifically developed to enable ‘socially cooperative dialogue’ – adaptive and aware conversational interaction in which mutual understanding is co-constructed and ensured collaboratively. The technical approach is described and results of evaluation studies are reported

A Two-Study Approach to Explore the Effect of User Characteristics on Users’ Perception and Evaluation of a Virtual Assistant’s Appearance

This research investigates the effect of different user characteristics on the perception and evaluation of an agent’s appearance variables. Therefore, two different experiments have been conducted. In a 3 × 3 × 5 within-subjects design (Study 1; N = 59), three different target groups (students, elderly, and cognitively impaired people) evaluated 30 different agent appearances that varied in species (human, animal, and robot) and realism (high detail, low detail, stylized shades, stylized proportion, and stylized shade with stylized proportion). Study 2 (N = 792) focused on the effect of moderating variables regarding the same appearance variables and aims to supplement findings of Study 1 based on a 3 × 5 between-subjects design. Results showed effects of species and realism on person perception, users’ liking, and using intention. In a direct comparison, a higher degree of realism was perceived as more positive, while those effects were not replicated in Study 2. Further on, a majority evaluated nonhumanoid agents more positively. Since no interaction effects of species and realism have been found, the effects of stylization seem to equally influence the perception for all kind of species. Moreover, the importance of the target group’s preference was demonstrated, since differences with regard to the appearance evaluation were found

A Two-Study Approach to Explore the Effect of User Characteristics on Users’ Perception and Evaluation of a Virtual Assistant’s Appearance

This research investigates the effect of different user characteristics on the perception and evaluation of an agent’s appearance variables. Therefore, two different experiments have been conducted. In a 3 × 3 × 5 within-subjects design (Study 1; N = 59), three different target groups (students, elderly, and cognitively impaired people) evaluated 30 different agent appearances that varied in species (human, animal, and robot) and realism (high detail, low detail, stylized shades, stylized proportion, and stylized shade with stylized proportion). Study 2 (N = 792) focused on the effect of moderating variables regarding the same appearance variables and aims to supplement findings of Study 1 based on a 3 × 5 between-subjects design. Results showed effects of species and realism on person perception, users’ liking, and using intention. In a direct comparison, a higher degree of realism was perceived as more positive, while those effects were not replicated in Study 2. Further on, a majority evaluated nonhumanoid agents more positively. Since no interaction effects of species and realism have been found, the effects of stylization seem to equally influence the perception for all kind of species. Moreover, the importance of the target group’s preference was demonstrated, since differences with regard to the appearance evaluation were found

What are you Grateful for? Enhancing Gratitude Routines by Using Speech Assistants

This paper presents an extension for Amazon’s Alexa, which provides a gratitude journal, and investigates its effectiveness compared to a regular paper-based version. Decades of research demonstrate that expressing gratitude has various psychological and physical benefits. At the same time, gratitude routines run the risk of being a hassle activity, which diminishes the positive outcome. Speech assistants might help to integrate gratitude routines more easily in an intuitive way using voice input. The results of our 8-day field study with two experimental groups (Alexa group vs. Paper group, N = 8) show that users see the benefits, that Alexa was effective in reducing participants’ stress and that both groups express their gratitude differently. The positive effect of Alexa was restricted by a security setting (limiting user input to eight seconds) imposed by Amazon, which has now been repealed. The findings give practical and theoretical implications of how verbal gratitude expression affects participants’ well-being