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