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The Social Signal Processing Network

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.

For more details, read the research vision of the SSPNet, as stated in the Belfast Declaration

What are Social Signals?

A social signal is a communicative or informative signal that, either directly or indirectly, provides information concerning social interactions, social emotions, social attitudes or social relations. Social signals are manifested through a multiplicity of non-verbal behavioural cues including facial expressions, body postures, gestures, vocal outbursts, etc.

What is Social Signal Processing?

Social Signal Processing lies at the intersection of three main domains:

  • Conceptual Modelling. The interactions and social relations that people have with each other are generally governed by principles and laws. The SSPNet investigates these laws, makes them explicit, and studies how these laws are expressed and influenced by social signals
  • Automatic Analysis. Social interactions can be sensed with a wide array of devices (cameras, microphones, proximity detectors, smartphones, etc.). The SSPNet investigates automatic approaches aimed at understanding social signals captured with sensors
  • Synthesis. Artificial agents display a wide spectrum of artificially generated nonverbal behavioural cues. The SSPNet investigates how these synthetic cues can be made capable of conveying social signals eliciting desired social perceptions

As a result, Social Signal Processing addresses three main research questions:

  1. Is it possible to identify, describe and conceptualize social signalling patterns that are stable at least for a given context and culture?
  2. Is it possible to automatically detect and understand nonverbal behavioural cues conveying social signals captured with sensors like microphones and cameras?
  3. Is it possible to synthesize nonverbal behavioural cues conveying desired social signals for embodiment of social behaviours in artificial agents, robots or other manufacts?

For more details about question 1 see the following:

For more details about question 2, see the following:

For more details about question 3, see the following

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