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Intelligent Virtual Agents are suitable means for interactive storytelling for children. The engagement level of child interaction with virtual agents is a challenging issue in this area. However, the characteristics of child-agent interaction received moderate to little attention in scientific studies whereas such knowledge may be crucial to design specific applications. This article proposes a Wizard of Oz platform for interactive narration. An experimental study in the context of interactive storytelling exploiting this platform is presented to evaluate the impact of agent prosody and facial expressions on child participation during storytelling. The results show that the use of the virtual agent with prosody and facial expression modalities improves the engagement of children in interaction during the narrative sessions. CCS CONCEPTS • Human-centered computing → User studies; Human computer interaction (HCI);

The analysis and simulation of the interactions that occur in group situations is important when humans and artificial agents, physical or virtual, must coordinate when inhabiting similar spaces or even collaborate, as in the case of human-robot teams. Artificial systems should adapt to the natural interfaces of humans rather than the other way around. Such systems should be sensitive to human behaviors, which are often social in nature, and account for human capabilities when planning their own behaviors. A limiting factor relates to our understanding of how humans behave with respect to each other and with artificial embodiments, such as robots. To this end, we present CongreG8 (pronounced ‘con-gre-gate’), a novel dataset containing the full-body motions of free-standing conversational groups of three humans and a newcomer that approaches the groups with the intent of joining them. The aim has been to collect an accurate and detailed set of positioning, orienting and full-body behaviors when a newcomer approaches and joins a small group. The dataset contains trials from human and robot newcomers. Additionally, it includes questionnaires about the personality of participants (BFI-10), their perception of robots (Godspeed), and custom human/robot interaction questions. An overview and analysis of the dataset is also provided, which suggests that human groups are more likely to alter their configuration to accommodate a human newcomer than a robot newcomer. We conclude by providing three use cases that the dataset has already been applied to in the domains of behavior detection and generation in real and virtual environments. A sample of the CongreG8 dataset is available at https://zenodo.org/record/4537811.

Figure 1: A participant's view of the small group scenario as they approach. The agent shown on the left in each case invites the participant to join the group by conducting verbal and non-verbal behaviors related to the following politeness strategies, from left to right: (a) not face-threatening act (NOT); (b) indirect (IND); (c) negative (NEG); (d) positive (POS); (e) direct (DIR).

Verbal and non-verbal behaviors that we use in order to effectively communicate with other people are vital for our success in our daily lives. Despite the importance of social skills, creating standardized methods for training them and supporting their training is challenging. Information and Communications Technology (ICT) may have a good potential to support social and emotional learning (SEL) through virtual social demonstration games. This paper presents initial work involving the design of a pedagogical scenario to facilitate teaching of socially appropriate and inappropriate behaviors when entering and standing in a small group of people, a common occurrence in collaborative social situations. This is achieved through the use of virtual characters and, initially, virtual reality (VR) environments for supporting situated learning in multiple contexts. We describe work done thus far on the demonstrator scenario and anticipated potentials, pitfalls and challenges involved in the approach.