Two-Layer Fuzzy Multiple Random Forest for Speech Emotion Recognition

Abstract

The two-layer fuzzy multiple random forest (TLFMRF) is proposed for speech emotion recognition. When recognizing speech emotion, there are some problems. One is that feature extraction relies on personalized features. The other is that emotion recognition doesn’t consider the differences among different categories of people. In the proposal, personalized and non-personalized features are fused for speech emotion recognition. High dimensional emotional features are divided into different subclasses by adopting the fuzzy C-means clustering algorithm, and multiple random forest is used to recognize different emotional states. Finally, a TLFMRF is established. Moreover, a separate classification of certain emotions which are difficult to recognize to some extent is conducted. The results show that the TLFMRF can identify emotions in a stable manner.