Prosody based attitude recognition with feature selection and its application to spoken dialog system as para-linguistic information

In this paper, prosody-based attitude recognition and its application to a spoken dialog system are proposed. Paralinguistic information plays a important role in the human communication. We aimed to recognize the user's attitude by prosody, and apply it to a spoken dialog system as para-linguistic information. In order to find important features to recognize the attitude from automatically extracted features, we applied some feature selection methods. Experimental results show the stepwise method, a combination of the forward selection method and the backward selection method, achieved the best recognition rate. Finally, the dialog system using the recognition results as para-linguistic information is shown.