1. A method for emotion recognition based on a minimum classification error, the method comprising: extracting a feature vector for emotion recognition based on a voice signal generated from a speaker and a galvanic skin response of the speaker; classifying a neutral emotion using a Gaussian mixture model based on the extracted feature vector for emotion recognition; and classifying other emotions except the previously classified neutral emotion using a Gaussian Mixture Model to which a discriminative weight for minimizing the loss function of a classification error for the feature vector for emotion recognition is applied.