• 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