• DocumentCode
    1792264
  • Title

    Blind signal separation for speech signals with noise

  • Author

    Shuping Lv ; Cheng Zhang

  • Author_Institution
    Coll. of Autom., Harbin Eng. Univ., Harbin, China
  • fYear
    2014
  • fDate
    3-6 Aug. 2014
  • Firstpage
    1850
  • Lastpage
    1855
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation (ICMA), 2014 IEEE International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4799-3978-7
  • Type

    conf

  • DOI
    10.1109/ICMA.2014.6885983
  • Filename
    6885983