A Hybrid Emotion Recognition on Android Smart Phones

Awareness of emotion status of people is fairly important for aged ones, the ones with sub-health status, and various patients in order to keep them in good mood. The emotion recognition at run time is intrinsically challenging due to its complexity nature. On the one hand, the awareness of human emotion should be achieved as non-intrusive as possible. On the other hand, the android smart phones on the market are increasingly popular which are equipped with various sensors that can be used to achieve the awareness of emotion status. In this paper, we propose an approach based on the heart beat rate and contents of user´s talk, which are obtained from built-in camera and microphone on smart phones. We first classify anger, joy, normal, and sadness based on heart rates, then the emotion recognition is further improved by emotional key words in a talk. We have evaluated this approach in terms of recognition accuracy and power consumption found that the accuracy can achieve 84.7%.