Emotional Hindi speech: Feature extraction and classification

After the reliable commercial use of speech based processing be it text to speech conversion vice-versa, Interactive response system, product marketing or speech based search. Researchers are now focused on to the study of the emotional content of speech signals, and hence, many systems have been proposed for the classification and identification of the emotional content of a spoken utterance. In this paper attempt are made to present the features of emotional Hindi language, for identification and classification. Speech databases have been used for speech recognition, speech synthesis, speaker recognition, language translation, emotion recognition, emotion conversion. An attempt has been made classify emotional speech corpus developed at IPEC. A study is also preformed to understand the effect of feature selection in emotion identification and classification. Emotional speech classification is preformed on the basis of LPCC and MFCC features are also performed using K-mean cluster analysis.