Speech Emotion Recognition Using Gaussian Mixture Model

The importance of automatically recognizing emotions in human speech has grown with the increasing role of spoken language interfaces in human-computer interaction applications.In this paper, a emotion classification method base on GMM is presented.Five primary human emotions, including anger, surprise, happiness, neutral and sadness, are investigated.For speech emotion recognition, we combined 60 basic features to form the feature vector.Finally, the features of the speech were extracted by PCA were sent into the improved GMM for classification and recognition.Results show that the selected features are robust and effective for the emotion recognition .