Emotional Valence Recognition on Virtual, Robotic, and Human Faces: a Comparative Study
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Emotional Valence Recognition on Virtual, Robotic, and Human Faces: a Comparative Study Lisa Cerda 1
&
Pierluigi Graziani 1,2 & Jonathan Del-Monte 1,2
Received: 2 May 2020 / Revised: 25 September 2020 / Accepted: 1 October 2020 # Springer Nature Switzerland AG 2020
Abstract With the advent of new technologies in everyday life, leisure, or therapy, we will increasingly interact with a non-human virtual character. Understanding facial expressions and intentions of these virtual agents is important to enable them to achieve their goals. The objective of our study is to assess whether expressions are perceived as being positive or negative on faces more or less similar to those of humans. Eighty-three undergraduate students took part in a computerized emotion recognition task. The participants had to identify whether each face expressed a positive or a negative emotion. Eight different faces (human, avatar, mesh, and robot) were shown 38 times each on a computer screen. Each face was represented by a photo. Response time and the number of correct responses were recorded. Our research has raised important points: the accuracy and time taken for emotion recognition were found to be similar on human or avatar faces. On the other hand, as soon as these faces were too ambiguous or schematic, emotion recognition capacities were found to be diminished. Keywords Avatar . Emotion recognition . Facial expression
Introduction Humans communicate in sophisticated ways through many channels such as sound, vision, and even touch. This is how they convey important information. The spoken language occupies such an important place that we sometimes forget the importance of non-verbal signs. However, facial expressions play a major role in social interactions (Adolphs 1999). They make it possible to convey messages and information essential for survival (i.e., fear) or more broadly for communication allowing empathy (Frith 2009). The ability to recognize and understand facial expressions is therefore essential for social relationships. This is a universal skill for social interaction
* Lisa Cerda [email protected] Pierluigi Graziani [email protected] Jonathan Del-Monte [email protected] 1
Laboratoire de Psychologie Sociale (LPS), Aix-Marseille Université, 29 Avenue Robert Schuman, 13621 Aix-en-Provence, France
2
Université de Nîmes, 5 rue du Dr Georges Salan, 30021 Nîmes, France
(Ekman 1993). The processing of emotional expressions involves several subcortical regions such as the amygdala and occipital and temporal cortex regions (Dubal et al. 2011). In general, humans recognize positive facial expressions faster than negative expressions because they do not require the analysis of the whole face (i.e., just a smiling mouth can signify joy) (Leppänen and Hietanen 2004). With the advent of new technologies, such as virtual reality, augmented reality, and artificial intelligence, we can wonder whether humans are capable of the same performance in recognizing emotions in robots and avatars. Artificial ag
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