An extraction of emotion in human speech using speech synthesize and classifiers for each emotion

Authors:
Masaki Kurematsu;Jun Hakura;Hamido Fujita
Affiliations:
Faculty of Software and Information, Iwate Prefectual University, Iwate, Japan;Faculty of Software and Information, Iwate Prefectual University, Iwate, Japan;Faculty of Software and Information, Iwate Prefectual University, Iwate, Japan
Venue:
WSEAS Transactions on Information Science and Applications
Year:
2008

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Abstract

The typical method of estimation of emotion in speech has the 3 steps. First, researchers collect a lot of human speech. Next, researchers get speech features from human speech using frequency analysis and calculate the statistical value of them. Finally they make a classifier from the statistical value using a learning algorithm. Most researchers consider the collection of human speech, feature selection and learning algorithm to increase the validity of estimation. But the validity of estimation is not high. In this paper, we propose the 3 new methods to enhance the typical method of estimation of emotion in speech. First method is that we use synthetic speech to make a classifier. Second method is that we use not only mean and maximum but also Standard Deviation (SD), skewness and kurtosis to make a classifier. Third method is that we use the classifier for each emotion. In order to evaluate our approach, we did experiments. Experimental results show the possibility in which our approach is effective for improving the former method.