Automatic Text-Independent Emotion Recognition Using Spectral Features

In this paper we explored different spectral features such as MFCC, pitch chroma, skewness and centroid for emotion recognition. The emotions considered in this study are Fear, Anger, Neutral, and Happy. The system is evaluated for various combinations of spectral features. It is established that the combination of MFCC and skewness gave better recognition performance when compared with other combinations. These experiments are conducted and evaluated using Gaussian Mixture models (GMMs). The data base used in this study is Telugu emotion speech corpus (IIIT-KGP).