ABSTRACT
Affective computing is considered one of the important areas in the field of human and computer interaction where software systems can recognize and understand human's behaviour and emotions. Affective computing integrates a variety of modalities of inputs that are used to recognize users' emotions and consequently respond to these emotions accordingly. In this paper, we first conducted a broad survey of the varieties of modalities that are used for incorporating affective computing in software systems. We then discussed, classified, and critically analyzed the different approaches in this field that can be used and incorporated in order to detect, analyze, and respond to users' inputs efficiently. The contribution of this paper is providing an up-to-date review about the current literature and discussing the current challenges that lead to some insights into the future work that can be done to make affective computing more effective.
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Index Terms
- A Survey of Incorporating Affective Computing for Human-System Co-adaptation
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