Application of Hilbert marginal spectrum in speech emotion recognition

Marginal spectrum of the emotional speech is obtained through Hilbert-Huang Transform.Speech signals of four different emotions,namely happy,angry,boring and natrual,are analyzed contrastively focusing on the characteristics of the marginal spectrum.Then four features:SE,DSE,SECC and DSECC are extracted for emotion recognition.Finally speaker-independent and text-independent emotion recognitions are simulated by using these features respectively,which gains the best recognition rate of 90%,which is 22 percentage higher than Fourier Transform based feature MFCC.Thus,conclusion is drawn that HHT marginal spectrum can well reflect the emotional information in speech.