Title from publisher's bibliographic system (viewed on 17 Jul 2017).

What does it mean to be social? distinguishing social from biological signal systems -- Universal dimensions of social cognition -- Measuring responses to nonverbal social signals: research on affect receiving ability -- Computational analysis of vocal expression of affect - trends and challenges -- The vertical dimension of social signaling -- Self-presentation: signaling personal and social characteristics -- Interaction coordination and adaptation -- Social signals and persuasion -- Social presence in CMC and VR -- Facial actions as social signals -- Automatic analysis of bodily social signals -- Computational approaches for personality prediction -- Automatic analysis of aesthetics: human beauty, attractiveness, and likability -- Interpersonal synchrony: from social perception to social interaction -- Automatic analysis of social emotions -- Social signal processing for automatic role recognition -- Machine learning methods for social signal processing -- Speech synthesis: state-of-the-art and challenges for the future -- Body movements generation for virtual characters and social robots -- Approach and dominance as social signals for affective interfaces -- Virtual reality and prosocial behaviour -- Social signal processing in social robotics -- Social signal processing for surveillance -- Analysis of small groups -- Multimedia implicit tagging -- Social signal processing for conflict analysis and understanding -- Social signal processing and socially assistive robotics in developmental disorders -- Social signal of deception and dishonesty.

Social Signal Processing is the first book to cover all aspects of the modeling, automated detection, analysis, and synthesis of nonverbal behavior in human-human and human-machine interactions. Authoritative surveys address conceptual foundations, machine analysis and synthesis of social signal processing, and applications. Foundational topics include affect perception and interpersonal coordination in communication; later chapters cover technologies for automatic detection and understanding such as computational paralinguistics and facial expression analysis and for the generation of artificial social signals such as social robots and artificial agents. The final section covers a broad spectrum of applications based on social signal processing in healthcare, deception detection, and digital cities, including detection of developmental diseases and analysis of small groups. Each chapter offers a basic introduction to its topic, accessible to students and other newcomers, and then outlines challenges and future perspectives for the benefit of experienced researchers and practitioners in the field.