scholarly journals Nonverbal Social Sensing in Action: Unobtrusive Recording and Extracting of Nonverbal Behavior in Social Interactions Illustrated with a Research Example

2014 ◽  
Vol 38 (2) ◽  
pp. 231-245 ◽  
Author(s):  
Denise Frauendorfer ◽  
Marianne Schmid Mast ◽  
Laurent Nguyen ◽  
Daniel Gatica-Perez
Keyword(s):  
Social Interactions ◽  
Nonverbal Behavior ◽  
Social Sensing

scholarly journals Despite Appearances: Comparing Emotion Recognition in Abstract and Humanoid Avatars Using Nonverbal Behavior in Social Virtual Reality

2021 ◽  
Vol 2 ◽  
Author(s):  
Yilu Sun ◽  
Andrea Stevenson Won
Keyword(s):  
Virtual Reality ◽  
Social Interactions ◽  
Social Presence ◽  
Nonverbal Behavior ◽  
Emotional States ◽  
Face To Face ◽  
Social Closeness ◽  
Similar Information ◽  
Individual Measure ◽  
And Behavior

The ability to perceive emotional states is a critical part of social interactions, shaping how people understand and respond to each other. In face-to-face communication, people perceive others’ emotions through observing their appearance and behavior. In virtual reality, how appearance and behavior are rendered must be designed. In this study, we asked whether people conversing in immersive virtual reality (VR) would perceive emotion more accurately depending on whether they and their partner were represented by realistic or abstract avatars. In both cases, participants got similar information about the tracked movement of their partners’ heads and hands, though how this information was expressed varied. We collected participants’ self-reported emotional state ratings of themselves and their ratings of their conversational partners’ emotional states after a conversation in VR. Participants’ ratings of their partners’ emotional states correlated to their partners’ self-reported ratings regardless of which of the avatar conditions they experienced. We then explored how these states were reflected in their nonverbal behavior, using a dyadic measure of nonverbal behavior (proximity between conversational partners) and an individual measure (expansiveness of gesture). We discuss how this relates to measures of social presence and social closeness.

Predictive Validity of Thin-Slice Nonverbal Behavior from Social Interactions

2018 ◽  
Vol 45 (7) ◽  
pp. 983-993 ◽  
Author(s):  
Nora A. Murphy ◽  
Judith A. Hall ◽  
Mollie A. Ruben ◽  
Denise Frauendorfer ◽  
Marianne Schmid Mast ◽  
...  
Keyword(s):  
Social Interactions ◽  
Predictive Validity ◽  
Nonverbal Behavior ◽  
Thin Slice

scholarly journals Nonverbal Social Sensing: What Social Sensing Can and Cannot Do for the Study of Nonverbal Behavior From Video

2021 ◽  
Vol 12 ◽  
Author(s):  
Laetitia Aurelie Renier ◽  
Marianne Schmid Mast ◽  
Nele Dael ◽  
Emmanuelle Patricia Kleinlogel
Keyword(s):  
Nonverbal Behavior ◽  
New Technologies ◽  
Research Field ◽  
Video Data ◽  
Social Sensing ◽  
Promising Tool ◽  
Ubiquitous Sensing ◽  
Video Recordings ◽  
Social Signal ◽  
Approaches To Study

The study of nonverbal behavior (NVB), and in particular kinesics (i.e., face and body motions), is typically seen as cost-intensive. However, the development of new technologies (e.g., ubiquitous sensing, computer vision, and algorithms) and approaches to study social behavior [i.e., social signal processing (SSP)] makes it possible to train algorithms to automatically code NVB, from action/motion units to inferences. Nonverbal social sensing refers to the use of these technologies and approaches for the study of kinesics based on video recordings. Nonverbal social sensing appears as an inspiring and encouraging approach to study NVB at reduced costs, making it a more attractive research field. However, does this promise hold? After presenting what nonverbal social sensing is and can do, we discussed the key challenges that researchers face when using nonverbal social sensing on video data. Although nonverbal social sensing is a promising tool, researchers need to be aware of the fact that algorithms might be as biased as humans when extracting NVB or that the automated NVB coding might remain context-dependent. We provided study examples to discuss these challenges and point to potential solutions.

scholarly journals Effect of Behavioral Realism on Social Interactions Inside Collaborative Virtual Environments

2020 ◽  
Vol 27 (2) ◽  
pp. 163-182 ◽  
Author(s):  
Fernanda Herrera ◽  
Soo Youn Oh ◽  
Jeremy N. Bailenson
Keyword(s):  
Social Interactions ◽  
Virtual Environments ◽  
Social Presence ◽  
Nonverbal Behavior ◽  
Interpersonal Attraction ◽  
Arm Movements ◽  
Head Movements ◽  
The Other ◽  
Dyadic Interaction ◽  
Collaborative Virtual Environments

Collaborative virtual environments (CVEs), wherein people can virtually interact with each other via avatars, are becoming increasingly prominent. However, CVEs differ in type of avatar representation and level of behavioral realism afforded to users. The present investigation compared the effect of behavioral realism on users' nonverbal behavior, self-presence, social presence, and interpersonal attraction during a dyadic interaction. Fifty-one dyads (aged 18 to 26) embodied either a full-bodied avatar with mapped hands and inferred arm movements, an avatar consisting of only a floating head and mapped hands, or a static full-bodied avatar. Planned contrasts compared the effect of behavioral realism against no behavioral realism, and compared the effect of low versus high behavioral realism. Results show that participants who embodied the avatar with only a floating head and hands experienced greater social presence, self-presence, and interpersonal attraction than participants who embodied a full-bodied avatar with mapped hands. In contrast, there were no significant differences on these measures between participants in the two mapped-hands conditions and those who embodied a static avatar. Participants in the static-avatar condition rotated their own physical head and hands significantly less than participants in the other two conditions during the dyadic interaction. Additionally, side-to-side head movements were negatively correlated with interpersonal attraction regardless of condition. We discuss implications of the finding that behavioral realism influences nonverbal behavior and communication outcomes.

Perceived Voice Disorders in Older Adults and Impact on Social Interactions

2021 ◽  
pp. 1-8
Author(s):  
Connie K. Porcaro ◽  
Clare Singer ◽  
Boris Djokic ◽  
Ali A. Danesh ◽  
Ruth Tappen ◽  
...  
Keyword(s):  
Older Adults ◽  
Social Interactions ◽  
Social Engagement ◽  
Leisure Activities ◽  
Treatment Strategies ◽  
Voice Disorders ◽  
Community Dwelling ◽  
Vocal Performance ◽  
Older Individuals ◽  
Cross Sectional

Purpose Many aging individuals, even those who are healthy, report voice changes that can impact their ability to communicate as they once did. While this is commonly reported, most do not seek evaluation or management for this issue. The purpose of this study was to investigate the prevalence and differences in voice disorders in older adults, along with the effect of fatigue on their social interactions. Method This is a cross-sectional investigation of a community-dwelling sample of individuals aged 60 years or older. Participants completed the Questionnaire on Vocal Performance, the Social Engagement Index subset “Engagement in Social or Leisure Activities,” and the Fatigue Severity Scale. Results Results indicated 32.5% of the 332 participants reported symptoms of voice problems with no difference found between male and female respondents. A slight increase in report of voice problems was noted with each year of age. Participants who self-reported voice problems indicated less interaction in social activities involving communication than those who did not. Finally, as severity of self-reported voice problems increased, an increase was reported by the same individuals for signs of fatigue. Conclusions Voice problems and resulting decreased social interaction are commonly experienced by older individuals. Voice symptoms in older adults have been found to benefit from evidence-based treatment strategies. It is critical to provide education to encourage older individuals to seek appropriate evaluation and management for voice issues through a speech-language pathologist or medical professional.

“Shhhh! Alex Has Something To Say”: AAC-SGD Use in the Classroom Setting

2010 ◽  
Vol 19 (4) ◽  
pp. 108-114 ◽  
Author(s):  
Lisa M. Mellman ◽  
Laura S. DeThorne ◽  
Julie A. Hengst
Keyword(s):  
Social Interaction ◽  
Social Interactions ◽  
Augmentative And Alternative Communication ◽  
Classroom Community ◽  
Classroom Observations ◽  
Classroom Teachers ◽  
Classroom Setting ◽  
Alternative Communication ◽  
Structured Interviews ◽  
Missed Opportunities

Abstract The present qualitative study was designed to examine augmentative and alternative communication (AAC) practices, particularly surrounding speech-generating devices (SGDs), in the classroom setting. We focused on three key child participants, their classroom teachers, and associated speech-language pathologists across three different schools. In addition to semi-structured interviews of all participants, six classroom observations per child were completed. Data were coded according to both pre-established and emergent themes. Four broad themes emerged: message-focused AAC use, social interactions within the classroom community, barriers to successful AAC-SGD use, and missed opportunities. Findings revealed a lack of SGD use in the classroom for two children as well as limited social interaction across all cases. We conclude by highlighting the pervasive sense of missed opportunities across these classroom observations and yet, at the same time, the striking resiliency of communicative effort in these cases.

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