DocumentCode
2612970
Title
Speech enhancement through nonlinear adaptive source separation methods
Author
Doukas, Nikos ; Stathaki, Tania ; Naylor, Patrick
Author_Institution
Dept. of Electr. Eng., Imperial Coll. of Sci., Technol. & Med., London, UK
fYear
1996
fDate
24-26 Jun 1996
Firstpage
279
Lastpage
282
Abstract
A new method that exploits the ideas of independent source separation in the context of speech enhancement in single sensor signals, is developed and tested in various situations. The channel distortions of the two sensor case are artificially reproduced by suitable linear and nonlinear filters. Separation is implemented via a Lagrange neural network. Results on speech signals are shown
Keywords
adaptive signal processing; filtering theory; neural nets; nonlinear filters; speech enhancement; telecommunication channels; Lagrange neural network; channel distortions; independent source separation; linear filters; nonlinear adaptive source separation methods; nonlinear filters; sensor signals; speech enhancement; Adaptive signal processing; Artificial neural networks; Educational institutions; Lagrangian functions; Neural networks; Nonlinear distortion; Nonlinear filters; Source separation; Speech enhancement; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal and Array Processing, 1996. Proceedings., 8th IEEE Signal Processing Workshop on (Cat. No.96TB10004
Conference_Location
Corfu
Print_ISBN
0-8186-7576-4
Type
conf
DOI
10.1109/SSAP.1996.534871
Filename
534871
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