Speech is a most popular biometrics nowadays used for human interaction. An emotion is a mental and a physiological state of a person. Emotion Based Speaker Recognition has attracted many researchers. Emotions are associated with the variety of feelings and thoughts. An emotion based speaker recognition system, recognizes the person's emotionsbased on pitch, speaking style, intensity, sampling frequency. Mel frequency CepstralCoefficient is the first step in a speaker recognition system. In this paper, we are implementing the gender - based modified MFCC approach to differentiate the individuals. For the classification purpose we have used the K-means algorithm.

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Emotionrecognition From Speech fourier Transform Traditional Mfcc Modern Mfccapproach nearest Neighboralgorithm K-means Vector Quantization.