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Emotion expression is an essential function for daily life that can be severely affected some psychological disorders. In this paper we identified seven emotional states anger, surprise, sadness, happiness, fear, disgust and neutral. The definition of parameters is a crucial step in the development of a system for emotion analysis. The 15 explored features are energy intensity, pitch, standard deviation, jitter, shimmer, autocorrelation, noise to harmonic ration, harmonic to noise ration, energy entropy block, short term energy, zero crossing rate, spectral roll-off, spectral centroid and spectral flux, and formants In this work database used is SAVEE (Surrey audio visual expressed emotion). Results by using different learning methods and estimation is done by using a confidence interval for identified parameters are compared and explained. The overall experimental results reveals that Model 2 and Model 3 give better results than Model 1 using learning methods and estimation shows that most emotions are correctly estimated by using energy intensity and pitch.