Speech Emotion Recognition Based on SVM and GMM-HMM Hybrid System

Speech emotion recognition is one of the latest challenges in speech processing, we implemented a hybrid system for speech emotion recognition. Two methods were proposed, compared and combined. At first, we utilized GMM-HMM model fed with MFCC feature to exploit the dynamics of emotional signals. Then a balanced SVM classifier was applied on the static LLD feature. In order to take advantage of generative model and discriminate model, these two methods were combined by taking the probability representation of the GMM-HMM model as the additional features for the SVM classifier. This hybrid system makes full use of both MFCC feature and LLD feature, the performance of the hybrid system also proves the effectiveness of our proposed system.