Interpreting social cues to generate credible affective reactions of   virtual job interviewers
  In this paper we describe a mechanism of generating credible affective reactions in a virtual recruiter during an interaction with a user. This is done using communicative performance computation based on the behaviours of the user as detected by a recognition module. The proposed software pipeline is part of the TARDIS system which aims to aid young job seekers in acquiring job interview related social skills. In this context, our system enables the virtual recruiter to realistically adapt and react to the user in real-time. 
Hazael Jones, Nicolas Sabouret, Ionut Damian, Tobias Baur, Elisabeth   Andr\'e, Ka\'ska Porayska-Pomsta and Paola Rizzo
cs.AI cs.CY