Social signal processing: Survey of an emerging domain

被引:567
作者
Vinciarelli, Alessandro [1 ,2 ]
Pantic, Maja [3 ,4 ]
Bourlard, Herve [1 ,2 ]
机构
[1] IDIAP Res Inst, CH-1920 Martigny, Switzerland
[2] Ecole Polytech Fed Lausanne, CH-1015 Lausanne, Switzerland
[3] Univ London Imperial Coll Sci Technol & Med, London SW7 2AZ, England
[4] Univ Twente, NL-7522 NB Enschede, Netherlands
基金
欧洲研究理事会; 瑞士国家科学基金会;
关键词
Social signals; Computer vision; Speech processing; Human behaviour analysis'; Social interactions; EMOTION RECOGNITION; FACE DETECTION; AUTOMATIC-ANALYSIS; GAIT RECOGNITION; THIN SLICES; SELF; COMMUNICATION; EXPRESSIONS; BEHAVIOR; SPEECH;
D O I
10.1016/j.imavis.2008.11.007
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 turn taking, 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. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:1743 / 1759
页数:17
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