Emotion Analysis from Speech of Different Age Groups

This Recognition of speech emotion based on suitable features provides age information that helps the society in different ways. As the length and shape of human vocal tract and vocal folds vary with age of the speaker, the area remains a challenge. Emotion recognition system based on speaker’s age will help criminal investigators, psychologists and law enforcement agencies in dealing with different segments of the society. Particularly child psychologists, counselors can take timely preventive measures based on such recognition system. The area remains further complex since the recognition system trained for adult users performs poorer when it involves children. This has motivated the authors to move in this direction. A novel effort is made in this work to determine the age of speaker based on emotional speech prosody and clustering them using fuzzy c-means algorithm. The results are promising and we are able to demarcate the emotional utterances based on age.

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