Using Big Data for Emotionally Intelligent Mobile Services through Multi-Modal Emotion Recognition - Baimbetov, Yerzhan; Khalil, Ismail; Steinbauer, Matthias; Anderst-Kotsis, Gabriele (Inclusive Smart Cities and e-Health, 2015)
Humans express and perceive emotional states in multi-modal fashion such as facial, acoustic expressions, gesture, and posture. Our task as AI researchers is to give computers the ability to communicate with users in consideration of their emotions. In recognition of a subject’s emotions, it is significantly important to be aware of the emotional context. Thanks to the advancement of mobile technology, it is feasible to collect contextual data. In this paper, the authors descibe the first step to extract insightful emotional information using cloud-based Big Data infrastructure. Relevant aspects of emotion recognition and challenges that come with multi-modal emotion recognition are also discussed.