Title :
Blind signal separation for speech signals with noise
Author :
Shuping Lv ; Cheng Zhang
Author_Institution :
Coll. of Autom., Harbin Eng. Univ., Harbin, China
Abstract :
Blind signal separation methods are diverse and almost studied in no noise situations, while the noise exists in practice. In this paper, firstly we designed an FIR filter and applied it to remove the added Gaussian noise in the observed signals. And then we improved the standard natural gradient algorithm (SNG) and named it as an improved natural gradient algorithm (ING). Lastly we used Fast ICA algorithm, the SNG and the ING to separate the mixed signals which were processed by the FIR filter. We contrasted and analogized the signal interference ration (SIR) of results of the three algorithms above. We obtained that it´s helpful for separation to filter the observed signals under low signal to noise ration (SNR) circumstance, however under the high SNR circumstance, the filtering operation doesn´t improve the separation property.
Keywords :
FIR filters; blind source separation; filtering theory; gradient methods; independent component analysis; signal denoising; speech processing; FIR filter; SIR; added Gaussian noise removal; blind signal separation methods; fast ICA algorithm; improved natural gradient algorithm; independent component analysis; signal interference ration; signal-to-noise ration; speech signals; standard natural gradient algorithm; Algorithm design and analysis; Blind source separation; Finite impulse response filters; Signal processing algorithms; Signal to noise ratio; Blind signal separation; FIR filter; Fast ICA; Natural gradient algorithm; Normal noise;
Conference_Titel :
Mechatronics and Automation (ICMA), 2014 IEEE International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4799-3978-7
DOI :
10.1109/ICMA.2014.6885983