The TARDIS project aims to build a scenario-based serious-game simulation platform for NEETs and job-inclusion associations that supports social training and coaching in the context of job interviews. This paper presents the general architecture of the TARDIS job interview simulator, and the serious game paradigm that we are developing. 1 NEET is a government acronym for young people not in employment, education or training. 2 ec.europa.eu/eurostat 3

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This paper presents an approach that makes use of a virtual character and social signal processing techniques to create an immersive job interview simulation environment. In this environment, the virtual character plays the role of a recruiter which reacts and adapts to the user's behavior thanks to a component for the automatic recognition of social cues (conscious or unconscious behavioral patterns). The social cues pertinent to job interviews have been identified using a knowledge elicitation study with real job seekers. Finally, we present two user studies to investigate the feasibility of the proposed approach as well as the impact of such a system on users.

Previous studies have shown that the success of interpersonal interaction depends not only on the contents we communicate explicitly, but also on the social signals that are conveyed implicitly. In this paper, we present NovA (NOnVerbal behavior Analyzer), a system that analyzes and facilitates the interpretation of social signals conveyed by gestures, facial expressions and others automatically as a basis for computer-enhanced social coaching. NovA records data of human interactions, automatically detects relevant behavioral cues as a measurement for the quality of an interaction and creates descriptive statistics for the recorded data. This enables us to give a user online generated feedback on strengths and weaknesses concerning his social behavior, as well as elaborate tools for offline analysis and annotation.

Individualized virtual agents can enhance the user's perception of a virtual scenario. However, most systems only provide customization for visual features of the characters. In this paper, we describe an approach to individualizing the non-verbal behavior of virtual agents.To this end, we present a software framework which is able to visualize individualized non-verbal behavior. For demonstration purposes, we designed four behavioral profiles that simulate prototypical behaviors for differences in personality and gender. These were then tested in an evaluation study.

The outcome of interpersonal interactions depends not only on the contents that we communicate verbally, but also on nonverbal social signals. Because a lack of social skills is a common problem for a significant number of people, serious games and other training environments have recently become the focus of research. In this work, we present NovA (Nonverbal behavior Analyzer), a system that analyzes and facilitates the interpretation of social signals automatically in a bidirectional interaction with a conversational agent. It records data of interactions, detects relevant social cues, and creates descriptive statistics for the recorded data with respect to the agent's behavior and the context of the situation. This enhances the possibilities for researchers to automatically label corpora of human-agent interactions and to give users feedback on strengths and weaknesses of their social behavior.

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Automatic detection and interpretation of social signals carried by voice, gestures, mimics, etc. will play a key-role for next-generation interfaces as it paves the way towards a more intuitive and natural human-computer interaction. The paper at hand introduces Social Signal Interpretation (SSI), a framework for real-time recognition of social signals. SSI supports a large range of sensor devices, filter and feature algorithms, as well as, machine learning and pattern recognition tools. It encourages developers to add new components using SSI's C++ API, but also addresses front end users by offering an XML interface to build pipelines with a text editor. SSI is freely available under GPL at http://openssi.net.