DocumentCode :
3277084
Title :
Overcomplete ICA algorithm of speech signal extraction in underdetermined mixtures
Author :
Baiyan, Li ; Jinhua, Tian
Author_Institution :
Dept. of Inf. Eng., Huang Huai Univ., Zhumadian, China
fYear :
2011
fDate :
15-17 April 2011
Firstpage :
1520
Lastpage :
1522
Abstract :
An overcomplete ICA algorithm was presented based on the geometric algorithm and shortest-path algorithm for underdetermined blind source separation, i.e. observed signal numbers are less than sources numbers. The algorithm is used to extract speech signal. In speech signals processing, speech signals are collected by microphones, and then use algorithms to extract and separate, when the number of speakers more than the number of microphones. Experimental results indicate that the proposed method has good effect.
Keywords :
blind source separation; independent component analysis; speech processing; blind source separation; geometric algorithm; overcomplete ICA algorithm; shortest path algorithm; signal numbers; sources numbers; speech signal extraction; speech signals processing; underdetermined mixtures; Algorithm design and analysis; Clustering algorithms; Microphones; Signal processing algorithms; Simulation; Speech; Speech processing; Independent component analysis(ICA); Speech signal extraction; overcomplete ICA; underdetermined;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-8036-4
Type :
conf
DOI :
10.1109/ICEICE.2011.5777453
Filename :
5777453
Link To Document :
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