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Structure of combining support vector machine (SVM) and DBN. Speech features are converted into deep features by a pre-trained DBN, which are feature vectors output by the last hidden layer of the DBN. The feature vectors act as the input of SVM and are used to train the SVM. The output of the SVM classifier is the emotion status corresponding to the input speech sample.
