Title: Building an Emotionally Responsive Avatar with Dynamic Facial Expressions in Human—Computer Interactions
The role of affect has been long studied in human–computer interactions. Unlike previous studies that focused on seven basic emotions, an avatar named Diana was introduced who expresses a higher level of emotional intelligence. To adapt to the users various affects during interaction, Diana simulates emotions with dynamic facial expressions. When two people collaborated to build blocks, their affects were recognized and labeled using the Affdex SDK and a descriptive analysis was provided. When participants turned to collaborate with Diana, their subjective responses were collected and the length of completion was recorded. Three modes of Diana were involved: a flat-faced Diana, a Diana that used mimicry facial expressions, and a Diana that used emotionally responsive facial expressions. Twenty-one responses were collected through a five-point Likert scale questionnaire and the NASA TLX. Results from questionnaires were not statistically different. However, the emotionally responsive Diana obtained more positive responses, and people spent the longest time with the mimicry Diana. In post-study comments, most participants perceived facial expressions on Diana’s face as natural, four mentioned uncomfortable feelings caused by the Uncanny Valley effect. more »« less
Nam_Kim, Hyung
(, British Journal of Visual Impairment)
Many people including those with visual impairment and blindness take advantage of video conferencing tools to meet people. Video conferencing tools enable them to share facial expressions that are considered as one of the most important aspects of human communication. This study aims to advance knowledge of how those with visual impairment and blindness share their facial expressions of emotions virtually. This study invited a convenience sample of 28 adults with visual impairment and blindness to Zoom video conferencing. The participants were instructed to pose facial expressions of basic human emotions (anger, fear, disgust, happiness, surprise, neutrality, calmness, and sadness), which were video recorded. The facial expressions were analyzed using the Facial Action Coding System (FACS) that encodes the movement of specific facial muscles called Action Units (AUs). This study found that there was a particular set of AUs significantly engaged in expressing each emotion, except for sadness. Individual differences were also found in AUs influenced by the participants’ visual acuity levels and emotional characteristics such as valence and arousal levels. The research findings are anticipated to serve as the foundation of knowledge, contributing to developing emotion-sensing technologies for those with visual impairment and blindness.
BACKGROUND Facial expressions are critical for conveying emotions and facilitating social interaction. Yet, little is known about how accurately sighted individuals recognize emotions facially expressed by people with visual impairments in online communication settings. OBJECTIVE This study aimed to investigate sighted individuals’ ability to understand facial expressions of six basic emotions in people with visual impairments during Zoom calls. It also aimed to examine whether education on facial expressions specific to people with visual impairments would improve emotion recognition accuracy. METHODS Sighted participants viewed video clips of individuals with visual impairments displaying facial expressions. They then identified the emotions displayed. Next, they received an educational session on facial expressions specific to people with visual impairments, addressing unique characteristics and potential misinterpretations. After education, participants viewed another set of video clips and again identified the emotions displayed. RESULTS Before education, participants frequently misidentified emotions. After education, their accuracy in recognizing emotions improved significantly. CONCLUSIONS This study provides evidence that education on facial expressions of people with visual impairments can significantly enhance sighted individuals’ ability to accurately recognize emotions in online settings. This improved accuracy has the potential to foster more inclusive and effective online interactions between people with and without visual disabilities.
Kim, Hyung Nam; Sutharson, Sam Jotham
(, British Journal of Visual Impairment)
People can visualize their spontaneous and voluntary emotions via facial expressions, which play a critical role in social interactions. However, less is known about mechanisms of spontaneous emotion expressions, especially in adults with visual impairment and blindness. Nineteen adults with visual impairment and blindness participated in interviews where the spontaneous facial expressions were observed and analyzed via the Facial Action Coding System (FACS). We found a set of Action Units, primarily engaged in expressing the spontaneous emotions, which were likely to be affected by participants’ different characteristics. The results of this study could serve as evidence to suggest that adults with visual impairment and blindness show individual differences in spontaneous facial expressions of emotions.
Hou, Tianyu; Adamo, Nicoletta; Villani, Nicholas
(, AHFE International)
The overall goal of our research is to develop a system of intelligent multimodal affective pedagogical agents that are effective for different types of learners (Adamo et al., 2021). While most of the research on pedagogical agents tends to focus on the cognitive aspects of online learning and instruction, this project explores the less-studied role of affective (or emotional) factors. We aim to design believable animated agents that can convey realistic, natural emotions through speech, facial expressions, and body gestures and that can react to the students’ detected emotional states with emotional intelligence. Within the context of this goal, the specific objective of the work reported in the paper was to examine the extent to which the agents’ facial micro-expressions affect students’ perception of the agents’ emotions and their naturalness. Micro-expressions are very brief facial expressions that occur when a person either deliberately or unconsciously conceals an emotion being felt (Ekman &Friesen, 1969). Our assumption is that if the animated agents display facial micro expressions in addition to macro expressions, they will convey higher expressive richness and naturalness to the viewer, as “the agents can possess two emotional streams, one based on interaction with the viewer and the other based on their own internal state, or situation” (Queiroz et al. 2014, p.2).The work reported in the paper involved two studies with human subjects. The objectives of the first study were to examine whether people can recognize micro-expressions (in isolation) in animated agents, and whether there are differences in recognition based on the agent’s visual style (e.g., stylized versus realistic). The objectives of the second study were to investigate whether people can recognize the animated agents’ micro-expressions when integrated with macro-expressions, the extent to which the presence of micro + macro-expressions affect the perceived expressivity and naturalness of the animated agents, the extent to which exaggerating the micro expressions, e.g. increasing the amplitude of the animated facial displacements affects emotion recognition and perceived agent naturalness and emotional expressivity, and whether there are differences based on the agent’s design characteristics. In the first study, 15 participants watched eight micro-expression animations representing four different emotions (happy, sad, fear, surprised). Four animations featured a stylized agent and four a realistic agent. For each animation, subjects were asked to identify the agent’s emotion conveyed by the micro-expression. In the second study, 234 participants watched three sets of eight animation clips (24 clips in total, 12 clips per agent). Four animations for each agent featured the character performing macro-expressions only, four animations for each agent featured the character performing macro- + micro-expressions without exaggeration, and four animations for each agent featured the agent performing macro + micro-expressions with exaggeration. Participants were asked to recognize the true emotion of the agent and rate the emotional expressivity ad naturalness of the agent in each clip using a 5-point Likert scale. We have collected all the data and completed the statistical analysis. Findings and discussion, implications for research and practice, and suggestions for future work will be reported in the full paper. ReferencesAdamo N., Benes, B., Mayer, R., Lei, X., Meyer, Z., &Lawson, A. (2021). Multimodal Affective Pedagogical Agents for Different Types of Learners. In: Russo D., Ahram T., Karwowski W., Di Bucchianico G., Taiar R. (eds) Intelligent Human Systems Integration 2021. IHSI 2021. Advances in Intelligent Systems and Computing, 1322. Springer, Cham. https://doi.org/10.1007/978-3-030-68017-6_33Ekman, P., &Friesen, W. V. (1969, February). Nonverbal leakage and clues to deception. Psychiatry, 32(1), 88–106. https://doi.org/10.1080/00332747.1969.11023575 Queiroz, R. B., Musse, S. R., &Badler, N. I. (2014). Investigating Macroexpressions and Microexpressions in Computer Graphics Animated Faces. Presence, 23(2), 191-208. http://dx.doi.org/10.1162/
Solbu, Anne; Frank, Mark G.; Xu, Fei; Nwogu, Ifeoma; Neurohr, Madison
(, Journal of Nonverbal Behavior)
Meta-analyses have not shown emotions to be significant predictors of deception. Criticisms of this conclusion argued that individuals must be engaged with each other in higher stake situations for such emotions to manifest, and that these emotions must be evaluated in their verbal context (Frank and Svetieva in J Appl Res Memory Cognit 1:131–133, 10.1016/j.jarmac.2012.04.006, 2012). This study examined behavioral synchrony as a marker of engagement in higher stakes truthful and deceptive interactions, and then compared the differences in facial expressions of fear, contempt, disgust, anger, and sadness not consistent with the verbal content. Forty-eight pairs of participants were randomly assigned to interviewer and interviewee, and the interviewee was assigned to steal either a watch or a ring and to lie about the item they stole, and tell the truth about the other, under conditions of higher stakes of up to $30 rewards for successful deception, and $0 plus having to write a 15-min essay for unsuccessful deception. The interviews were coded for expression of emotions using EMFACS (Friesen and Ekman in EMFACS-7; emotional facial action coding system, 1984). Synchrony was demonstrated by the pairs of participants expressing overlapping instances of happiness (AU6 + 12). A 3 (low, moderate, high synchrony) × 2 (truth, lie) mixed-design ANOVA found that negative facial expressions of emotion were a significant predictor of deception, but only when they were not consistent with the verbal content, in the moderate and high synchrony conditions. This finding is consistent with data and theorizing that shows that with higher stakes, or with higher engagement, emotions can be a predictor of deception.
Wang, Heting, Gaddy, Vidya, Beveridge, James Ross, and Ortega, Francisco R. Building an Emotionally Responsive Avatar with Dynamic Facial Expressions in Human—Computer Interactions. Retrieved from https://par.nsf.gov/biblio/10494314. Multimodal Technologies and Interaction 5.3 Web. doi:10.3390/mti5030013.
Wang, Heting, Gaddy, Vidya, Beveridge, James Ross, & Ortega, Francisco R. Building an Emotionally Responsive Avatar with Dynamic Facial Expressions in Human—Computer Interactions. Multimodal Technologies and Interaction, 5 (3). Retrieved from https://par.nsf.gov/biblio/10494314. https://doi.org/10.3390/mti5030013
Wang, Heting, Gaddy, Vidya, Beveridge, James Ross, and Ortega, Francisco R.
"Building an Emotionally Responsive Avatar with Dynamic Facial Expressions in Human—Computer Interactions". Multimodal Technologies and Interaction 5 (3). Country unknown/Code not available: Multimodal Technologies and Interaction. https://doi.org/10.3390/mti5030013.https://par.nsf.gov/biblio/10494314.
@article{osti_10494314,
place = {Country unknown/Code not available},
title = {Building an Emotionally Responsive Avatar with Dynamic Facial Expressions in Human—Computer Interactions},
url = {https://par.nsf.gov/biblio/10494314},
DOI = {10.3390/mti5030013},
abstractNote = {The role of affect has been long studied in human–computer interactions. Unlike previous studies that focused on seven basic emotions, an avatar named Diana was introduced who expresses a higher level of emotional intelligence. To adapt to the users various affects during interaction, Diana simulates emotions with dynamic facial expressions. When two people collaborated to build blocks, their affects were recognized and labeled using the Affdex SDK and a descriptive analysis was provided. When participants turned to collaborate with Diana, their subjective responses were collected and the length of completion was recorded. Three modes of Diana were involved: a flat-faced Diana, a Diana that used mimicry facial expressions, and a Diana that used emotionally responsive facial expressions. Twenty-one responses were collected through a five-point Likert scale questionnaire and the NASA TLX. Results from questionnaires were not statistically different. However, the emotionally responsive Diana obtained more positive responses, and people spent the longest time with the mimicry Diana. In post-study comments, most participants perceived facial expressions on Diana’s face as natural, four mentioned uncomfortable feelings caused by the Uncanny Valley effect.},
journal = {Multimodal Technologies and Interaction},
volume = {5},
number = {3},
publisher = {Multimodal Technologies and Interaction},
author = {Wang, Heting and Gaddy, Vidya and Beveridge, James Ross and Ortega, Francisco R.},
}
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