Patent Document ID: 8180638
Application ID: 12711030
Patent Status: 1

Claim One:
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, the feature vector for emotion recognition including a voice signal feature vector containing information extracted from the voice signal of the speaker and a galvanic skin response feature vector extracted from 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 the 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, wherein the emotions are classified by comparing a likelihood ratio with a threshold value, and the likelihood ratio is obtained from the Gaussian Mixture Model modified by the discriminative weight.