Bridging the Gap between Social Animal and Unsocial Machine: A Survey of Social Signal Processing

Alessandro Vinciarelli, Maja Pantic, Dirk K.J. Heylen, Catherine Pelachaud, Isabella Poggi, Francesca D’Ericco, Marc Schröder

    Research output: Contribution to journalArticleAcademicpeer-review

    246 Citations (Scopus)

    Abstract

    Social Signal Processing is the research domain aimed at bridging the social intelligence gap between humans and machines. This paper is the first survey of the domain that jointly considers its three major aspects, namely, modeling, analysis, and synthesis of social behavior. Modeling investigates laws and principles underlying social interaction, analysis explores approaches for automatic understanding of social exchanges recorded with different sensors, and synthesis studies techniques for the generation of social behavior via various forms of embodiment. For each of the above aspects, the paper includes an extensive survey of the literature, points to the most important publicly available resources, and outlines the most fundamental challenges ahead.
    Original languageUndefined
    Pages (from-to)69-87
    Number of pages19
    JournalIEEE transactions on affective computing
    Volume3
    Issue number1
    DOIs
    Publication statusPublished - Jan 2012

    Keywords

    • Social Signal Processing
    • EWI-22959
    • social interactions understanding
    • IR-84219
    • nonverbal behavior analysis and synthesis
    • METIS-296251
    • HMI-MI: MULTIMODAL INTERACTIONS

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