Subtle Social Signal Processing

Subtle Social Signal Processing is concerned with the development of computational techniques which empower technologies to make sense of the subtle aspects of social context and the ingrained social signals. Here, the subtle social context refers to the internal mechanisms which enable or inhibit inter-personal collaborative processes and are grounded in personal intuitions, motivations and culture. It comprises of latent, non-verbal and transient social information which cannot be easily captured by external sensors. Examples of subtle social context include joint attention and action, inter-personal synchrony, empathy and social comfort. In order to conduct Subtle Social Signal Processing, we rely on wearable sensors which can be embedded in everyday objects such as textiles.

In the KInD group, we specifically focus on using wearable sensors embodied in emerging materials to a) develop a fine-grained understanding of latent and transient non-verbal social behaviors, b) conduct Subtle Social Signal Processing at-scale (i.e. for extended periods, with larger groups, and in-the-wild), and c) facilitate a sustained participation of communities in social sensing projects by co-designing responsible data acquisition, annotation, and analysis workflows. The particular application areas include sustainability, health and well being, and accessibility, and more recently we have started to examine applications of Subtle Social Signal Processing in blended social contexts.

We contribute by a) designing socially intelligent and responsive products, services and systems, b) establishing reliable proxies and ground truths for inter-personal collaborative processes derived using the physiological and physical data, and c) novel research tools and methods that enable designers and researchers to acquire contextualized social data at scale.

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