The ability to detect human emotion from their speech is going to be a great addition in the field of human-robot interaction. The aim of the work is to build an emotion recognition system using Mel-frequency cepstral coefficients (MFCC) and Gaussian mixture model (GMM) classifier. Basically the purpose of the work is aimed at describing the best possible and available methods for recognizing emotion from an emotional speech. For that reason already existing techniques and used methods for feature extraction and pattern classification have been reviewed and discussed in this paper.
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