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

Abstract

A novel speech enhancement method based on empirical mode decomposition is proposed. The method is a fully data driven approach. Noisy speech signal is decomposed adaptively into oscillatory components called Intrinsic Mode Functions (IMFs) using a process called sifting. The empirical mode decomposition denoising involves thresholding each IMFs. A nonlinear function is introduced for amplitude thresholding. And then reconstructs the estimated speech signal using the processed IMFs. The experimental results show significant improvement in output SNR and quality as compared to recently reported results.

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Authors and Affiliations

  1. The College Of Computer Science and Technology, Harbin Engineering University, NO.145 Nantong Street, Nangang District, Harbin, China
    Li-Ran Shen, Qing-Bo Yin, Xue-Yao Li & Hui-Qiang Wang

Authors

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

Editor information

Editors and Affiliations

  1. IRMAR, Université de Rennes, Campus de Beaulieu, 35042, Rennes Cedex, France
    Dima Grigoriev
  2. Intel Corporation, JF1-13, 2111 NE 25th Avenue, 97124, Hillsboro, OR, USA
    John Harrison
  3. Steklov Institute of Mathematics at St. Petersburg, 27 Fontanka, St., 191023, Petersburg, Russia
    Edward A. Hirsch

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© 2006 Springer-Verlag Berlin Heidelberg

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Shen, LR., Yin, QB., Li, XY., Wang, HQ. (2006). Speech Enhancement in Short-Wave Channel Based on Empirical Mode Decomposition. In: Grigoriev, D., Harrison, J., Hirsch, E.A. (eds) Computer Science – Theory and Applications. CSR 2006. Lecture Notes in Computer Science, vol 3967. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11753728\_59

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