This networking session aims at identifying future directions in affective and person-centred computing, by amalgamating related research findings within a unified knowledge framework. Such a framework would incorporate affect-aware, cognitive and behavioural models with results and knowledge on multimodal affect and context analysis, while being able to represent and handle uncertain and scalable affective knowledge and adapt it to specific user behaviours, contexts of interaction and environment changes.
Core participants to this session are world-leading researchers in the fields of recognition of emotion and affect, knowledge technologies and neural network and neural-symbolic learning and analysis; related developments will be based on the large experience gained by participation of partners to numerous EC projects, as well as state-of-the art standardisation (in the W3C framework) activities in the field of Knowledge Technologies.
Affective computing has been a topic of great interest during the last few years, researched across various disciplines, including perception, interpretation, cognition and interaction/expression. In this framework, many EU projects and networks have been funded to investigate different aspects of affective interaction, such as theories and computational models of emotion processes, databases, signal analysis and recognition, generation of embodied conversational agents (e.g. Ermis, Safira, Humaine, Semaine, etc.) Research results mostly refer to the analysis of affective and emotional theories and related computational models, extraction of affective cues from single or multi-sensorial inputs, modelling of affective states, analysis and recognition of user states based on extracted cues, generation of synthetic characters that communicate different expressive states and attitudes, generation of databases with affective interactions for training and testing the analysis and synthesis techniques and inclusion of the above in interactive environments. These activities have produced systems that model and analyse single or multi-modal affective cues, utilizing statistical information and rules for this purpose, data sets and environments used to perform user state detection, and interactive Embodied Conversational Agents.