DocumentCode :
3430254
Title :
Clipping detection of audio signals based on kernel Fisher discriminant
Author :
Feng Deng ; Chang-chun Bao ; Feng Bao
Author_Institution :
Speech & Audio Signal Process. Lab., Beijing Univ. of Technol., Beijing, China
fYear :
2013
fDate :
6-10 July 2013
Firstpage :
99
Lastpage :
103
Abstract :
In this paper, a kind of clipping detection method for audio signal is proposed based on kernel Fisher discriminant (KFD) in MDCT domain. The kernel method and the Fisher linear discriminant analysis (FLDA) are introduced to the proposed method. First, the clipping and non-clipping feature parameters are extracted using MDCT coefficients of audio signals. Next, the optimal projection vector and the classification threshold are obtained by training KFD based on the extracted feature parameters. Finally, the decision rule of KFD is employed to detect the clipping distortion. The test results indicate that the proposed algorithm yields good clipping detection result, the performance is better than the reference method.
Keywords :
audio signal processing; feature extraction; signal classification; signal detection; vectors; FLDA; Fisher linear discriminant analysis; MDCT coefficients; MDCT domain; algorithm yields; audio signals; classification threshold; clipping detection method; clipping distortion; decision rule; feature extraction; kernel Fisher discriminant; kernel method; nonclipping feature parameters; optimal projection vector; reference method; training KFD; Equations; Feature extraction; Kernel; Mathematical model; Reactive power; Support vector machine classification; Vectors; Clipping detection; FLDA; KFD; Kernel method; MDCT;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal and Information Processing (ChinaSIP), 2013 IEEE China Summit & International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/ChinaSIP.2013.6625306
Filename :
6625306
Link To Document :
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