Social Skills Training is often used in the multimodal Interaction research community as an umbrella term for systems that aim at training social skills: managing appropriately verbal and nonverbal behaviors when interacting with one or more persons, in relation with various communicative functions such as turn taking and emotions.

People with social affective deficits have difficulties controlling their own social behavior and also suffer from interpreting others' social behavior. Behavioral therapy (e.g. with a clinician) and Social Skills Training (SST) are used in medical settings. Patients are trained with a coach to experience social interaction and to reduce social stress. SST includes a role-play of a simulation of actual situations [1,2,3]. In addition to behavioral training, cognitive behavioral therapy [4] and motivational interviewing are also useful to better understand and train social-affective interaction. All these methods are effective but expensive and difficult to access.

This workshop is looking for works describing how interactive, multimodal technology such as virtual agents can be used in social skills training for measuring and training social-affective interactions [5]. Sensing technology now enables analyzing user's behaviors and physiological signals (heart-rate, EEG, etc.). Various signal processing and machine learning methods can be used for such prediction tasks. Beyond sensing, it is also important to analyze human behaviors and model and implement training methods (e.g. by virtual agents, social robots, relevant scenarios, design appropriate and personalized feedback about social skills performance). Such social signal processing and tools can be applied to measure and reduce social stress in everyday situations, including public speaking at schools and workplaces. Target populations include depression, Social Anxiety Disorder (SAD), Schizophrenia, Autism Spectrum Disorder (ASD), but also a much larger group of different social pathological phenomena.

In this workshop, we invite participants from academia, industry or clinical settings to present and discuss social-affective design of multimodal training for health.