ABSTRACT

Emotion based speaker Identification System is the process of automatically identifying speaker’s emotion based on features extracted from speech waves. This paper presents experiment with the building and testing of a Speaker’s emotion identification for Hindi speech using Mel Frequency Cepestral Coefficients and Vector Quantization techniques. We collected voice samples of Hindi speech sentences in four basic emotions to study speaker’s emotion identification and it was found that with proposed emo-voice model we are able to achieve accuracy of 73% of speaker’s emotion identification in speech out of 93% of the total speech samples provided to the system.