The category labels used are, the archetypal emotions of Anger, Disgust, Fear, Joy, Sadness and Surprise. The emotions are classified into six categories. The proposed method makes use of short time log frequency power coefficients (LFPC) to represent the speech signals and a discrete hidden Markov model (HMM) as the classifier. In this paper, a text independent method of emotion classification of speech is proposed. However, the performance of systems employing these features degrades substantially when more than two categories of emotion are to be classified.
In emotion classification of speech signals, the popular features employed are statistics of fundamental frequency, energy contour, duration of silence and voice quality.
0 kommentar(er)
