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신경회로망을 이용한 ARS 장애음성의 식별에 관한 연구
조철우,김광인,김대현,권순복,김기련,김용주,전계록,왕수건 한국음성과학회 2001 음성과학 Vol.8 No.2
Speech material, which is collected from AR (Automatic Response System), was analyzed and classified into disease and non-disease state. The material include 11 different kinds of diseases. Along with AR speech, DA` (igital Audio Tape) speech is collected in parallel to give the bench mark. To analyze speech material, analysis tools, which is developed local laboratory, are used to provide an improved and robust performance to the obtained parameters. To classify speech into disease and non-disease class, multi-layered neural network was used. Three different combinations of 3, G, 1 parameters are tested to obtain the proper network size and to find the best performance. From the experiment, the classification rate of 92.5% was obtained.