How a Virtual Agent Should Smile?
A smile may communicate different meanings depending on subtle characteristics of the facial expression. In this article, we have studied the morphological and dynamic characteristics of amused, polite, and embarrassed smiles displayed by a virtual agent.
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stract. A smile may communicate different meanings depending on subtle characteristics of the facial expression. In this article, we have studied the morphological and dynamic characteristics of amused, polite, and embarrassed smiles displayed by a virtual agent. A web application has been developed to collect virtual agent’s smile descriptions corpus directly constructed by users. Based on the corpora and using a decision tree classification technique, we propose an algorithm to determine the characteristics of each type of the smile that a virtual agent may express. The proposed algorithm enables one to generate a variety of facial expressions corresponding to the polite, embarrassed, and amused smiles. Keywords: Smile, Embodied Conversational Agent (ECA), Facial Expression, Decision Tree.
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Introduction
Smiling is one of the simplest and most easily recognized facial expressions [1]. Only one muscle, the zygomatic major, has to be activated to create a smile. But a smile may have several meanings – such as amusement, politeness, or embarrassment – depending on subtle characteristics of the smile itself and of other elements of the face that come with the smile. These different types of smile are often distinguished by humans during an interaction. Recently [2,3] has shown that people also distinguish different types of smile when they are expressed by a virtual agent. Moreover, a smiling virtual agent enhances the human-machine interaction, for instance the perception of the task, of the agent, and the motivation and enthusiasm of the user [4,5]. However, an inappropriate smile (an inappropriate type of smile or a smile expressed in an inappropriate situation) may have negative effects on the interaction [5]. In this paper, we present a research work that aimed at identifying the morphological and dynamic characteristics of different types of smile. More precisely, we have investigated how a virtual agent may display different types of smile in context-free situations. For this purpose, we have created a web application to J. Allbeck et al. (Eds.): IVA 2010, LNAI 6356, pp. 427–440, 2010. c Springer-Verlag Berlin Heidelberg 2010
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M. Ochs, R. Niewiadomski, and C. Pelachaud
collect a virtual agent’s smile descriptions corpus directly constructed by users. Based on the corpus, we have used a machine learning algorithm to determine the characteristics of each type of the smile that a virtual agent may express. As a result, we obtain the algorithm that may be easily implemented in any virtual agent. It enables one to generate a variety of facial expressions corresponding to the polite, embarrassed and amused smiles. The paper structure is as follow. After giving an overview of existing work on humans’ smiles (Section 2.1) and on virtual agents’ smiles (Section 2.2), we introduce the web application developed to collect the smiles corpus (Section 3). Section 4 describes the corpus. In Section 5, we present the algorithm to compute the smile’s characteristics based on the smiles corpus. We conclude in Section 6.
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