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Research Article | Open Access |

Implementation of Modified Wiener Filtering in Frequency Domain in Speech Enhancement

Author 1: C. Ramesh Kumar Author 2: M. P. Chitra
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 13, No. 2 · Published 2022

DOI: https://doi.org/10.14569/IJACSA.2022.0130251

Abstract

The most common complaint about Digital Hearing Aids is feedback noise. Many attempts have been undertaken in recent years to successfully reduce feedback noise. A wiener filter, which calculates the wiener gain using before and after filtering SNR, is one technique to reduce background noise. Modified Noise Reduction Method (MNRM), a new way for reducing feedback noise Reduction, is presented in this work. In the Modified Noise Reduction Strategy, the advantages of a wiener filter are merged with a decision-directed approach and a twin-stage noise suppression technique The Modified Noise Reduction method can reduce the noise more successfully, according to comprehensive MATLAB programming, investigation, and findings analysis. After being modelled in MATLAB for seven distinct noise types, the SNR of the two architectures is compared.

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How to Cite this Article

Kumar, C. R., & Chitra, M. P. (2022). Implementation of Modified Wiener Filtering in Frequency Domain in Speech Enhancement. International Journal of Advanced Computer Science and Applications, 13(2). https://doi.org/10.14569/IJACSA.2022.0130251

Kumar, C. Ramesh, and M. P. Chitra. "Implementation of Modified Wiener Filtering in Frequency Domain in Speech Enhancement." International Journal of Advanced Computer Science and Applications, vol. 13, no. 2, 2022, https://doi.org/10.14569/IJACSA.2022.0130251.

@article{Kumar2022,
  title     = {Implementation of Modified Wiener Filtering in Frequency Domain in Speech Enhancement},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {2},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {C. Ramesh Kumar and M. P. Chitra},
  doi       = {10.14569/IJACSA.2022.0130251},
  url       = {https://doi.org/10.14569/IJACSA.2022.0130251}
}

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