Speech Enhancement Using Empirical Mode Decomposition

Authors

  • V. Muni Kalyan Venkatesh  Department of Electronics and Communication Engineering, S.V. University College of Engineering, Tirupati, A.P.India
  • Dr. B. Anuradha  Professor, Department of Electronics and Communication Engineering, S.V. University College of Engineering, Tirupati, A.P. India

Keywords:

Polystyrene, Polymethyl Methacrylate, Polymer blends, AC conduction, Optical properties

Abstract

Empirical Mode Decomposition (EMD) [1], a multi-resolution method for reducing speech signal noise, is presented. The suggested technique for speech de-noising is entirely data-driven. Sifting is a temporal decomposition process that adaptively breaks down a noisy signal into oscillatory components known as Intrinsic Mode Functions (IMFs). The method's fundamental idea is to use a shrinkage function to threshold IMFs before reconstructing the signal. Speech with varying noise levels is subjected to the de-noising technique, and the outcomes are contrasted with wavelet compression. The research is limited to signals with white Gaussian noise additively present distorted in them. Afterwards, pitch is extracted from the de-noised signal using spectral pitch analysis.

References

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International Journal of Scientific Research in Science and Technology

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Published

2023-12-30

Issue

Volume 10, Issue 6, November-December-2023

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
V. Muni Kalyan Venkatesh, Dr. B. Anuradha "Speech Enhancement Using Empirical Mode Decomposition" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 10, Issue 6, pp.345-352, November-December-2023.