The workshop will take place in association with the 15th ACM International Conference on Multimodal Interaction (ICMI 2013), Sydney, Australia.

Organising Committee:

Kim Hartmann, Otto von Guericke University Magdeburg
Ronald Böck, Otto von Guericke University Magdeburg
Christian Becker-Asano, University of Freiburg
Jonathan Gratch, University of Southern California
Björn Schuller, Technical University Munich
Klaus R. Scherer, University of Geneva

Call for Papers

To develop user adaptable Human-Computer Interaction (HCI), the role of emotions occurring during interaction became increasingly valuable over the past years. Emotions, being widely accepted as essential to Human-Human interaction, became relevant for system designers of affective interfaces in order to provide natural, user-centred interaction. However, to adequately incorporate emotions in modern HCI systems, results from varying research disciplines must be combined.

An affective system must be able to detect, identify, process and respond to emotions occurring during HCI in realtime. Hence, the methods involved in emotion processing must be reliable, efficient and well-defined throughout the systems abstraction layers. In order to fulfil these requirements, conceptual work is needed to define suitable technical models on emotion, disposition and behaviour. To allow technical systems to automatically process and respond to emotions, the defined models must link machine-detectable, physical, human characteristics to abstract strategic algorithms and be consistent with the predominant emotion theories and observations.

Emotions occurring during HCI are detected feature-based, depending on the modalities provided and implying the necessity of identifying significant features. Furthermore, these features must be processed in an adequate way to allow the automatic distinguishing of emotions. In multi-modal systems sufficient fusion techniques must be defined to maximize the correctness of the emotion detection and synthesis. To respond to the detected emotions, the system should be provided with an artificial emotional intelligence. Artificial emotional intelligence in turn requires a combination of knowledge databases, history processing, plan construction, coping strategies, user models, emotion and behaviour theories.

Currently, several solutions on incorporating emotions in technical systems exist. These solutions depend heavily on the scope, application and modalities used. The applied concepts tend to be highly specific and layer dependent, often lacking universality and interoperability. However, to allow cognitive technical systems to become truly affective and user adaptable, all methods used must have a reliable theoretic foundation and cooperate.

Topics include, but are not limited to:

- Theoretic models of emotion in affective computing
- Role and models of emotion for cognitive modelling
- Best practice representations of emotions in HCI systems
- Processing of emotions during HCI
- Role and models of emotion in user modelling
- Emotion representation for knowledge bases
- Learning emotions: Strategies and representations
- Models on the perception of emotions and emotion synthesis
- Studies on emotion representations and their implications
- Applications

Prospective authors are invited to submit full papers (10 pages). Accepted papers will be published in the Springer LNCS Workshop Proceedings. All submissions should be anonymous and according to Springer LNCS specifications.

For further information please refer to http://erm4hci.kognitivesysteme.de