Gender-Driven Emotion Recognition Through Speech Signals for Ambient Intelligence Applications

This paper proposes a system that allows recognizing a person's emotional state starting from audio signal registrations. The provided solution is aimed at improving the interaction among humans and computers, thus allowing effective human-computer intelligent interaction. The system is able to recognize six emotions (anger, boredom, disgust, fear, happiness, and sadness) and the neutral state. This set of emotional states is widely used for emotion recognition purposes. It also distinguishes a single emotion versus all the other possible ones, as proven in the proposed numerical results. The system is composed of two subsystems: 1) gender recognition (GR) and 2) emotion recognition (ER). The experimental analysis shows the performance in terms of accuracy of the proposed ER system. The results highlight that the a priori knowledge of the speaker's gender allows a performance increase. The obtained results show also that the features selection adoption assures a satisfying recognition rate and allows reducing the employed features. Future developments of the proposed solution may include the implementation of this system over mobile devices such as smartphones.