Feature Extraction techniques for Classification of Emotions in Speech Signals

Automatic speech emotion recognition is a process of recognizing emotions in speech. This has wide applications in the area of phsycatrics help and in robotics’he human computer interaction the challenging area of research. Any effective HCI system has two sections Training and testing. The techniques used in the system are feature extraction and classification. This paper focuses on the brief introduction of the GFCC feature extraction, optimization algorithm and the back propagation neural network for the classification of the emotions in speech. Keywords— emotions in speech, emotion recognition, Back propagation, Gammatone Frequency Cepstral Coefficients, GFCC, Bacterial Forging optimization.