International audienceDatabases of spontaneous multimodal expressions of affective states occurring during a task are few. This paper presents a protocol for eliciting stress in a public speaking task. Behaviors of 19 participants were recorded via a multimodal setup including speech, video of the facial expressions and body movements, balance via a force plate, and physiological measures. Questionnaires were used to assert emotional states, personality profiles and relevant coping behaviors to study how participants cope with stressful situations. Several subjective and objective performances were also evaluated. Results show a significant impact of the overall task and conditions on the participants' emotional activation. The possible future use of this new multimodal emotional corpus is described

Personal agents gather information about users in a user profile. In this work, we propose a novel ontologybased user profile learning. Particularly, we aim to learn context-enriched user profiles using data mining techniques and ontologies. We are interested in knowing to what extent data mining techniques can be used for user profile generation, and how to utilize ontologies for user profile improvement. The objective is to semantically enrich a user profile with contextual information by using association rules, Bayesian networks and ontologies in order to improve agent performance. At runtime, we learn which the relevant contexts to the user are based on the user's behavior observation. Then, we represent the relevant contexts learnt as ontology segments. The encouraging experimental results show the usefulness of including semantics into a user profile as well as the advantages of integrating agents and data mining using ontologies.

In recent decades, many studies have shown that schizophrenia is associated with severe social cognitive impairments affecting key components, such as the recognition of emotions, theory of mind, attributional style, and metacognition. Most studies investigated each construct separately, precluding analysis of the interactive and immersive nature of real-life situation. Specialized batteries of tests are under investigation to assess social cognition, which is thought now as a link between neurocognitive disorders and impaired functioning. However, this link accounts for a limited part of the variance of real-life functioning. To fill this gap, advances in virtual reality and affective computing have made it possible to carry out experimental investigations of naturalistic social cognition, in controlled conditions, with good reproducibility. This approach is illustrated with the description of a new paradigm based on an original virtual card game in which subjects interpret emotional displays from a female virtual agent, and decipher her helping intentions. Independent variables concerning emotional expression in terms of valence and intensity were manipulated. We show how several useful dependant variables, ranging from classic experimental psychology data to metacognition or subjective experiences records, may be extracted from a single experiment. Methodological issues about the immersion into a simulated intersubjective situation are considered. The example of this new flexible experimental setting, with regards to the many constructs recognized in social neurosciences, constitutes a rationale for focusing on this potential intermediate link between standardized tests and real-life functioning, and also for using it as an innovative media for cognitive remediation.

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