关键词: 特征, 分类, 语音, 深度信念网络模型（DBN）, 受限玻尔兹曼机（RBM）

Abstract: Online artificial voice service has been expanded in the business activities. In order to provide better customer service, it is needed to do effective evaluation of the quality of voice service. The purpose is to change artificial voice services into text using voice recognition technology and then classify. Common text classification models are Naive Bayes, KNN, back propagation neural networks, support vector machines and other models that are more dependent on the characteristics of the speech text representation after pretreatment and prone to the curse of dimensionality, local optimization and long training time. The Deep Belief Network model（DBN） can learn from the characteristics expressed in the text preprocessed to feature a more essential representation which eases classifiers and avoids the problems of above models. After text of the artificial voice service, through the deep belief network model conversion feature representation and then classification, the final classification results than the direct use of text features classification model have slightly increased.

Key words: feature, classification, voice, Deep Belief Network model（DBN）, Restricted Boltzmann Machine（RBM）