Detection of emotion in analysis of speech using linear predictive coding techniques (L.P.C)

Abstract

Detection of Emotion by analysis of speech is important for identification of emotional state of person. This can be done using ‘Linear Predictive Techniques(LPC)’, which has different parameters like pitch, vocal tract spectrum, formant frequencies, Duration, MFCC etc. which are used for extraction of features from speech. TEO-CB-Auto-Env is the method which is non-linear method of features extraction. Analysis is done using TU-Berlin (Technical University of Berlin) German database. Here emotion recognition is done for different emotions like neutral, happy, disgust, sad, boredom and anger. Emotion recognition is used in lie detector, database access systems, and in military for recognition of soldiers' emotion identification during the war.