Demonstrations of SSPNet project

SSPNet (Social Signal Processing Network) is an European Network of Excellence (NoE) which addresses Social Signal Processing.

SSPNet activities revolve around two research foci selected for their primacy in our everyday life:

* Social Signal Processing in Human-Human Interaction
* Social Signal Processing in Human-Computer Interaction

Hence,the main focus of the SSPNet is on developing and validating the scientific foundations and engineering principles (including resources for experimentation) required to address the problems of social behaviour analysis,interpretation,and synthesis. The project focuses on multimodal approaches aimed at:(i) interpreting information for better understanding of human social signals and implicit intentions,and (ii) generating socially adept behaviour of embodied conversational agents. It will consider how we can model,represent,and employ human social signals and behaviours to design autonomous systems able to know,either through their design or via a process of learning,how to understand and respond to human communicative signals and behaviour.

Different types of virtual characters smiles

In this context, our focus of research is to study how humans-virtual characters communication can be facilitated by the appropriate non-verbal behaviours of the virtual characters. As a first step, we have studied different types of virtual characters smiles (amused smile, polite smile, etc). In the following videos, you can see different types of virtual characters smiles, as well as example of virtual characters which express different smiles when they tell a funny story.


Ochs, M., Niewiadomski, R., Pelachaud, C., How a Virtual Agent Should Smile? – Morphological and Dynamic Characteristics of Virtual Agent’s Smiles, in Proceedings of the 10th International Conference on Intelligent Virtual Agents, Philadelphia, USA, pp. 427-440, 2010.

Synchrony emergence between dialog partners

Another aspect of making humans-conversationnal agents communication easier, is to enable dynamics linked to the quality of the interaction to emerge within the dyad (or within the group of interactants). Among other, during dialog, synchrony between non-verbal behaviours of agents is characteristic of the quality of their communication, i.e. it depends on their mutual understanding and on the amount of information they exchange.

In the following videos, you can see synchrony appear between agents just by the settling of a coupling between them when they both understand and perceive each other.

Agents start the interaction di-synchronised and after a while stabilised in synchrony

Up-right agent does not understand what is said (impossible coupling), down-right agent understands what is said, sees the speaker but is not seen back (impossible coupling), up-left agent understands what is said, perceives and is perceived by the speaker (coupling and synchrony constitute the stable state of the dyad they form).


K. Prépin and C. Pelachaud, Shared Understanding and Synchrony Emergence: Synchrony as an Indice of the Exchange of Meaning between Dialog Partners, Third International Conference on Agents and Artificial Intelligence, ICAART2011, Rome, Italie, January 2011, pp. 1-10 [pdf]

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