Automatic recognition of emotion based on a cognitively motivated emotion annotation system

Emotion recognition is very important for the extraction of expressive information. In this paper, we provide a robust and versatile emotion annotation scheme that can not only annotate explicit and implicit expressions of emotion, but also can encode different levels of information for a given emotion content. In addition, taking cognitive psychologists’ theories into account, large and comparatively high-quality emotion corpora are automatically created to allow for emotion recognition in Chinese and English. Our annotation scheme can easily be adapted for different kinds of applications dealing with emotion, and, being generic, can also be applied to other languages. We also discuss the two kinds of emotion representations used in our corpus, namely, holistic and componential representations. We find that the two representations have their own qualities and shortcomings and that choosing between them ultimately depends mainly on the application type.