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Speech Enhancement in Short-Wave Channel Based on Empirical Mode Decomposition

  • Li-Ran Shen
  • Qing-Bo Yin
  • Xue-Yao Li
  • Hui-Qiang Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3967)

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.

Keywords

Speech Signal Empirical Mode Decomposition Minimum Mean Square Error Speech Enhancement Clean Speech 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Li-Ran Shen
    • 1
  • Qing-Bo Yin
    • 1
  • Xue-Yao Li
    • 1
  • Hui-Qiang Wang
    • 1
  1. 1.The College Of Computer Science and TechnologyHarbin Engineering UniversityHarbinChina

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