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15 - Interpersonal Synchrony: From Social Perception to Social Interaction
- from Part II - Machine Analysis of Social Signals
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- By Mohamed Chetouani, University Pierre et Marie Curie, Emilie Delaherche, University Pierre et Marie Curie, Guillaume Dumas, University Pierre et Marie Curie, David Cohen, University Pierre et Marie Curie
- Edited by Judee K. Burgoon, University of Arizona, Nadia Magnenat-Thalmann, Université de Genève, Maja Pantic, Imperial College London, Alessandro Vinciarelli, University of Glasgow
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- Book:
- Social Signal Processing
- Published online:
- 13 July 2017
- Print publication:
- 08 May 2017, pp 202-212
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- Chapter
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Summary
Introduction
Synchrony refers to individuals’ temporal coordination during social interactions (Cappella, 2005). The analysis of this phenomenon is complex, requiring the perception and integration of multimodal communicative signals. The evaluation of synchrony has received multidisciplinary attention because of its role in early development (Feldman, 2003), language learning (Goldstein, King, & West, 2003), and social connection (Harrist & Waugh, 2002). Initially, instances of synchrony were directly perceived in the data by trained observers. Several methods have been proposed to evaluate interactional synchrony, ranging from behavior microanalysis (Cappella, 1997) to global perception of synchrony (Bernieri, Reznick, & Rosenthal, 1988). Behavioral synchrony has now captured the interest of researchers in such fields as social signal processing, robotics, and machine learning (Prepin & Pelachaud, 2011; Kozima, Michalowski, & Nakagawa, 2009).
In this chapter, we focus especially on description and definition of synchrony for the development of computational models. The chapter begins with a review of evidences of interpersonal synchrony from different research domains (psychology, clinics, neuroscience and biology). Then, we introduce a working definition of interpersonal synchrony (see Proposed Definition). The chapter surveys evaluation models and methods from the literature of psychology (see Non-computational Methods of Synchrony Assessment) and social signal processing (see Fully Automatic Measures of Synchrony). Finally, the chapter discusses a number of challenges that need to be addressed (see Conclusions and Main Challenges).
Non-verbal Evidence of Interpersonal Synchrony
Among social signals, synchrony and coordination have been considered lately (Ramseyer & Tschacher, 2010; Delaherche et al., 2012). Condon and Ogston (1967) initially proposed a microanalysis of human behavior (body motion and speech intonation) and evidenced the existence of interactional synchrony, the coordination between listener's and speaker's body movements, or between the listener's body movement and the speaker's pitch and stress variations. Bernieri et al. (1988) define coordination as the “degree to which the behaviors in an interaction are non-random, patterned or synchronized in both form and timing”. (Kendon, 1970) raises fundamental questions about the condition of interactional synchrony arousal and its function in interaction. When he synchronizes with the speaker, the listener demonstrates his ability to anticipate what the speaker is going to say. In this way, he gives feedback to the speaker and smoothens the running of the encounter.
28 - Social Signal Processing and Socially Assistive Robotics in Developmental Disorders
- from Part IV - Applications of Social Signal Processing
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- By Mohamed Chetouani, University Pierre et Marie Curie, Sofiane Boucenna, University Pierre and Marie Curie, Laurence Chaby, University Pierre and Marie Curie, University Paris Descartes, Monique Plaza, University Pierre and Marie Curie, University Paris Descartes, David Cohen, University Pierre et Marie Curie
- Edited by Judee K. Burgoon, University of Arizona, Nadia Magnenat-Thalmann, Université de Genève, Maja Pantic, Imperial College London, Alessandro Vinciarelli, University of Glasgow
-
- Book:
- Social Signal Processing
- Published online:
- 13 July 2017
- Print publication:
- 08 May 2017, pp 389-403
-
- Chapter
- Export citation
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Summary
Introduction
Multimodal social-emotional interactions play a critical role in child development and this role is emphasized in autism spectrum disorders (ASD). In typically developing children, the ability to correctly identify, interpret, and produce social behaviors (Figure 28.1) is a key aspect for communication and is the basis of social cognition (Carpendale & Lewis, 2004). This process helps children to understand that other people have intentions, thoughts, and emotions and act as a trigger of empathy (Decety & Jackson, 2004; Narzisi et al., 2012). Social cognition includes the child's ability to spontaneously and correctly interpret verbal and nonverbal social and emotional cues (e.g., speech, facial and vocal expressions, posture and body movements, etc.); the ability to produce social and emotional information (e.g., initiating social contact or conversation); the ability to continuously adjust and synchronize behavior to others (i.e., parent, caregivers, peers); and the ability to make an adequate attribution about another's mental state (i.e., “theory of mind”).
Definitions and Treatments
ASDs are a group of behaviorally defined disorders with abnormalities or impaired development in two areas: (1) persistent deficits in social communication and social interaction and (2) restricted, repetitive patterns of behavior, interests, or activities. An individual with ASD has difficulty interacting with other people due to an inability to understand social cues as well as others’ behaviors and feelings. For example, children with ASD often have difficulty with cooperative play with other peers; they prefer to continue with their own repetitive activities (Baron-Cohen & Wheelwright, 1999). Persons with ASD evaluate both world and human behavior uniquely because they react in an abnormal way to input stimuli while there is problematic human engagement and inability to generalize the environment (Rajendran & Mitchell, 2000). Although ASD remains a devastating disorder with a poor outcome in adult life, there have been important improvements in treating ASD with the development of various therapeutic approaches (Cohen, 2012).
Successful autism “treatments” using educational interventions have been reported as recently as a decade ago (Murray, 1997). Since then, the literature devoted to the description and evaluation of interventions in ASD has become substantial over the last few years. From this literature, a number of conclusions can be drawn. First, there is increasing convergence between behavioral and developmental methods (Ospina et al., 2008).