Speech Enhancement in Short-Wave Channel Based on ICA in Empirical Mode Decomposition Domain (original) (raw)

Abstract

It is well known that the non-stationary noise is the most difficult to be removed in speech enhancement. In this paper a novel speech enhancement algorithm based on the empirical mode decomposition (EMD) and then ICA is proposed to suppress the non-stationary noise. The noisy speech is decomposed into components by the EMD and ICA-based vector space, and the components are processed and reconstructed, respectively, by distinguishing between voiced speech and unvoiced speech. There are no requirements of noise whitening and SNR pre-calculating. Experiments show that the proposed method performs well suppressing of the non-stationary noise in short-wave channel for speech enhancement.

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Authors and Affiliations

  1. College of Computer Science And Technology, Harbin Engineering University, No.145 Nantong Street, Nangang District, Harbin, China
    Li-Ran Shen, Xue-Yao Li, Qing-Bo Yin & Hui-Qiang Wang
  2. Div. of Electronic, Computer and Telecommunication Engineering, Pukyong National University, Busan, Korea
    Qing-Bo Yin

Authors

  1. Li-Ran Shen
  2. Xue-Yao Li
  3. Qing-Bo Yin
  4. Hui-Qiang Wang

Editor information

Editors and Affiliations

  1. Siemens Corporate Research, 755 College Road East, 08540, Princeton, NJ, USA
    Justinian Rosca
  2. Department of CSEE, Oregon Health and Science University, Portland, Oregon, USA
    Deniz Erdogmus
  3. Dep. of Electrical and Computer Engineering, University of Florida, Gainesville, Florida, USA
    José C. Príncipe
  4. McMaster University, 1280 Main Street West, L8S 4K1, Hamilton, Ontario, Canada
    Simon Haykin

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© 2006 Springer-Verlag Berlin Heidelberg

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Shen, LR., Li, XY., Yin, QB., Wang, HQ. (2006). Speech Enhancement in Short-Wave Channel Based on ICA in Empirical Mode Decomposition Domain. In: Rosca, J., Erdogmus, D., Príncipe, J.C., Haykin, S. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2006. Lecture Notes in Computer Science, vol 3889. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11679363\_88

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