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http://dx.doi.org/10.6109/jkiice.2011.15.10.2093

Classification of Speech and Car Noise Signals using the Slope of Autocovariances in Frequency Domain  

Kim, Seon-Il (거제대학교)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.15, no.10, 2011 , pp. 2093-2099 More about this Journal
Abstract
Speech signal and car noise signal such as muffler noise are segregated from the one which has both signals mixed using statistical method. To classify speech signal from the other in segregated signals, FFT coefficients were obtained for all segments of a signal where each segment consists of 128 elements of a signal. For several coefficients of FFT corresponding to the low frequencies of a signal, autocovariances are calculated between coefficients of same order of all segments of a signal. Then they were averaged over autocovariances. Linear equation was eatablished for the those autocovariances using the linear regression method for each siganl. The coefficient of the slope of the line gives reference to compare and decide what the speech signal is. It is what this paper proposes. The results show it is very useful.
Keywords
Speech Signal; ICA; Slope of Autocovariances; Segregation of Signals;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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