Year-end Sale % OFF 
Abstract
Human communication relies mostly on nonverbal signals expressed through body language. Facial expressions, in particular, convey emotional information that allows people involved in social interactions to mutually judge the emotional states and to adjust its behavior appropriately. First studies aimed at investigating the recognition of facial expressions were based on static stimuli. However, facial expressions are rarely static, especially in everyday social interactions. Therefore, it has been hypothesized that the dynamics inherent in a facial expression could be fundamental in understanding its meaning. In addition, it has been demonstrated that nonlinguistic and linguistic information can contribute to reinforce the meaning of a facial expression making it easier to be recognized. Nevertheless, few studies have been performed on realistic humanoid robots. This experimental work aimed at demonstrating the human-like expressive capability of a humanoid robot by examining whether the effect of motion and vocal content influenced the perception of its facial expressions. The first part of the experiment aimed at studying the recognition capability of two kinds of stimuli related to the six basic expressions (i.e. anger, disgust, fear, happiness, sadness, and surprise): static stimuli, that is, photographs, and dynamic stimuli, that is, video recordings. The second and third parts were focused on comparing the same six basic expressions performed by a virtual avatar and by a physical robot under three different conditions: (1) muted facial expressions, (2) facial expressions with nonlinguistic vocalizations, and (3) facial expressions with an emotionally neutral verbal sentence. The results show that static stimuli performed by a human being and by the robot were more ambiguous than the corresponding dynamic stimuli on which motion and vocalization were associated. This hypothesis has been also investigated with a 3-dimensional replica of the physical robot demonstrating that even in case of a virtual avatar, dynamic and vocalization improve the emotional conveying capability.
Highlights
Our ability to process facial information is so quick and apparently effortless that most people take it for granted
One of the most remarkable books about the study of facial expressions in humans is The Expression of the Emotions in Man and Animals written by Charles Darwin in 1872.2 The aim of the book was “to ascertain, independently of common opinion, how far particular movements of the features and gestures are really expressive of certain states of the mind.”[2]. Darwin was mainly interested in investigating the universality of emotional expressiveness and hypothesized that the so-called six basic expressions, that is, happiness, sadness, anger, fear, surprise, and disgust, contain emotion-specific patterns of facial elements which make them biologically determined and universally recognizable by all people in spite of race and culture
The experiment aimed at investigating whether the dynamics underlying human facial expressions entails advantages even in the case of an expressive humanoid robot and whether nonlinguistic vocalizations and verbal information influence the recognition of facial expressions performed by a humanoid robot in comparison with the same visual stimuli without auditory information
Summary
Our ability to process facial information is so quick and apparently effortless that most people take it for granted. Attentions used to understand the person, especially during social situations This has led to a huge interest in the scientific study of faces since the 1800s with the first books concerning systematic descriptions of the movements of the facial muscles.[1,2,3]. Based on the evidence that some facial expressions of emotion were universal,[4,5,6] in 1976, Ekman and Friesen developed a procedure for measuring visibly different facial movements based on an anatomical analysis of facial actions.[7] This method called Facial Action Coding System (FACS) aimed at describing any facial expression a human being can make in terms of anatomically based Action Units (AUs), that is, the unit of measurement defining an observable independent movement of the face. The FACS has become a standard widely used by scientists in emotion research field
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
