WACI 2011 committee

Abstract

Taking into account emotions, or more generally affects, is currently widely explored to improve the quality of human-machine interaction and to ease the communication with users or potential customers. Affective or emotional computing covers a wide range of issues, challenges and approaches, both for emotion simulation (in particular for new generations of intelligent agents), emotion elicitation, expression and recognition. The latter is declined along several types of modalities and media data, such as physiological signals, facial expressions, speech, text, images and video. Thus, affective computing raises new challenges for computational intelligence, regarding e.g. computational representations of emotions and affective states, on the basis of psychological models, the architecture of systems modeling and processing these concepts as well as dedicated machine learning techniques appropriate to deal with the specificity of the related data. gathers papers from the various disciplines contributing to the domain, offering an overview of the current state of the art on this challenging and fast developing field, including both emotion simulation and emotion recognition, in particular from textual data.