DocumentCode :
2497866
Title :
Speech stream detection based on higher-order statistics
Author :
Shen, Li-ran ; Li, Xue-Yao ; Wei, Wei ; Zhang, Ruso ; Wang, Hui-Qiang
Author_Institution :
Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., China
Volume :
5
fYear :
2003
fDate :
2-5 Nov. 2003
Firstpage :
3086
Abstract :
The aim of speech stream detection is to capture the speech stream whose coming is random. The idea of using Higher Order Statistics (HOS) for speech stream detection is based on exploiting the Gaussian suppression that allows the separation of speech from the noise. HOS have inherent properties that make them well suited when dealing with a mixture of Gaussian and nonGaussian process. In addition, the HOS of speech signals have distinctive features that may be exploited to lead a better estimation and a more accurate discrimination between speech and noise. This paper explores the fourth order cumulants of speech signal and presents a new algorithm for speech stream detection. The considerable experimental results in which data comes from the real recorded on spot, show the method performs well.
Keywords :
Gaussian processes; higher order statistics; signal processing; speech processing; Gaussian suppression; HOS; fourth order cumulants; higher order statistics; nonGaussian process; speech separation; speech signal; speech stream detection; Computer science; Educational institutions; Gaussian noise; Higher order statistics; Humans; Signal processing algorithms; Speech analysis; Speech enhancement; Speech processing; Working environment noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
Type :
conf
DOI :
10.1109/ICMLC.2003.1260108
Filename :
1260108
Link To Document :
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