What Should a Generic Emotion Markup Language Be Able to Represent?

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In the recent years, increasing attention has been paid to the area of affective computing, which deals with the complex phenomenon of human emotion. Therefore, a model for describing, structuring, and categorizing emotional states of users is required. The dimensional emotion theory is one of widely used theoretical foundations for categorization of emotions. According to the dimensional theory, emotional states are projected to the affective space, which has two dimensions: valence and arousal. In order to navigate in the affective space, Cartesian coordinate system is used, where emotion quality is defined by combination of valence and arousal. In this paper, we propose another representation of the affective space with polar coordinate system. The key advantages of such a representation include (1) capability to account not only for emotion quality, but also for emotion intensity, (2) reasonable explanation of the location of neutral emotion in the affective space, and (3) straightforward interpretation of the meaning of an emotional state (quality defined by angle and intensity defined by distance from the origin). Although in our experiment most of the induced emotions can be differentiated with polar coordinate system, further investigation is still needed to find out either Cartesian or polar coordinates system represents affective space better in practice.

A major building block for the construction of reliable statistical classifiers in the context of affective human-computer interaction is the collection of training samples that appropriately reflect the complex nature of the desired patterns. This is especially in this application a non-trivial issue as, even though it is easily agreeable that emotional patterns should be incorporated in future computer operating, it is by far not clear how it should be realized. There are still open questions such as which types of emotional patterns to consider together with their degree of helpfulness for computer interactions and the more fundamental question on what emotions do actually occur in this context. In this paper we start by reviewing existing corpora and the respective techniques for the generation of emotional contents and further try to motivate and establish approaches that enable to gather, identify and categorize patterns of human-computer interaction.

Arxiv preprint arXiv:0912.1810, 2009

The ability of an intelligent environment to connect and adapt to real internal sates, needs and behaviors' meaning of humans can be made possible by considering users' emotional states as contextual parameters. In this paper, we build on enactive psychology and investigate the incorporation of emotions in pervasive systems. We define emotions, and discuss the coding of emotional human markers by smart environments. In addition, we compare some existing works and identify how emotions can be detected and modeled by a pervasive system in order to enhance its service and response to users. Finally, we analyze closely one XML-based language for representing and annotating emotions known as EARL and raise two important issues which pertain to emotion representation and modeling in XML-based languages.

Intelligent Virtual …, 2005

In this paper we present a two-steps approach towards the creation of affective Embodied Conversational Agents (ECAs): annotation of a real-life non-acted emotional corpus and animation by copy-synthesis. The basis of our approach is to study how coders perceive and annotate at several levels the emotions observed in a corpus of emotionally rich TV video interviews. We use their annotations to specify the expressive behavior of an agent at several levels. We explain how such an approach can be useful for providing knowledge as input for the specification of non-basic patterns of emotional behaviors to be displayed by the ECA (e.g. which perceptual cues and levels of annotation are required for enabling the proper recognition of the emotions).

Arxiv preprint arXiv:0912.2479, 2009

The ability of an intelligent environment to connect and adapt to real internal sates, needs and behaviors' meaning of humans can be made possible by considering users' emotional states as contextual parameters. In this paper, we build on enactive psychology and investigate the incorporation of emotions in pervasive systems. We define emotions, and discuss the coding of emotional human markers by smart environments. In addition, we compare some existing works and identify how emotions can be detected and modeled by a pervasive system in order to enhance its service and response to users. Finally, we analyze closely one XML-based language for representing and annotating emotions known as EARL and raise two important issues which pertain to emotion representation and modeling in XML-based languages.

Lecture Notes in Computer Science, 2008

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