Social Signal Processing: State-of-the-Art and Future Perspectives of an Emerging Domain

Alessandro Vinciarelli, Maja Pantic, Hervé Bourlard, Alex Pentland

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    98 Citations (Scopus)


    The ability to understand and manage social signals of a person we are communicating with is the core of social intelligence. Social intelligence is a facet of human intelligence that has been argued to be indispensable and perhaps the most important for success in life. This paper argues that next-generation computing needs to include the essence of social intelligence – the ability to recognize human social signals and social behaviours like politeness, and disagreement – in order to become more effective and more efficient. Although each one of us understands the importance of social signals in everyday life situations, and in spite of recent advances in machine analysis of relevant behavioural cues like blinks, smiles, crossed arms, laughter, and similar, design and development of automated systems for Social Signal Processing (SSP) are rather difficult. This paper surveys the past efforts in solving these problems by a computer, it summarizes the relevant findings in social psychology, and it proposes a set of recommendations for enabling the development of the next generation of socially-aware computing.
    Original languageUndefined
    Title of host publicationProceedings of the 16th ACM International Conference on Multimedia (MM'08)
    Place of PublicationNew York
    PublisherAssociation for Computing Machinery
    Number of pages10
    ISBN (Print)978-1-60558-303-7
    Publication statusPublished - Oct 2008
    Event16th ACM International Conference on Multimedia, MM 2008 - Vancouver, Canada
    Duration: 26 Oct 200831 Oct 2008
    Conference number: 16

    Publication series



    Conference16th ACM International Conference on Multimedia, MM 2008
    Abbreviated titleMM


    • EWI-14816
    • EC Grant Agreement nr.: FP6/0027787
    • METIS-255091
    • IR-62673
    • Algorithms
    • EC Grant Agreement nr.: FP7/211486

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