In last two decades automatic emotion recognition based on speech become wide area of research for human-machine communication. Many systems has been implemented to recognize emotion in speech signals. In this paper previously implemented speech emotion recognition systems has been reviewed using various types of classifiers. The classifiers used to distinguish emotions such as neutral ,surprise ,anger ,happy, sad, fearful, disgust ,etc. emotional speech samples are used as database for emotion recognition from speech and extracted features from speech samples are prosodic and spectral features such as pitch, energy, formants, speech rate ,(MFCC) Mel frequency cepstrum coefficient and linear prediction cepstrum coefficient (LPCC). the performance of classifiers represented by extracted features. Advantages and performance of speech emotion recognition system using different types of classifiers are also discussed.

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Emotion recognition Feature extraction Feature Selection spectral features prosodic features Classifier.