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Audio Quality Enhancement Using Adaptive Filters

Amit Kukker Yash Nigam Tushar Sawle Rajeet Kumar

Subject area: Science,Engineering and Technology  ·  Area of research: Electrical Engineering

Abstract

Audio quality enhancing plays a vital role in the field of speech recognition, communication, medical etc. The most widely used method is an optimal linear filtering that can reduce the noise level present in an audio signal and improve its signal to noise ratio (SNR). Here, we propose Adaptive LMS filtering method that can improve SNR and enhance audio quality in a very fruitful manner. The signal is filtered at once and the filter coefficients are computed adaptively in an exponential algorithm. The simulation results show a higher audio quality than the raw noise signal. Almost all practical signalling applications are difficult to implement. In this article, we propose a method to reduce noise in audio or speech signals using LMS adaptive filtering algorithms. The signal is filtered at once and the filter coefficients are computed adaptively in an exponential algorithm. The simulation results show a higher quality than the raw noise signal.

References

[1] International Journal of Modern Engineering Research (IJMER) Vol.2, Issue.3, May-June 2012 pp-792-795 ISSN: 2249-6645

[2] Adaptive Filter Theory by Simen Haykin: 3rd edition, Pearson Education Asia.LPE.

[3] B. Widow, "Adaptive noise canceling: principles and applications", Proceedings of the IEEE, vol. 63, pp. 1692- 1716, 1975.

[4] G. Goodwin, K. Sin, Adaptive Filtering, Prediction and Control, Englewood Cliffs, Prentice Hall, 1985.

[5] Jingdong, C., Jacob, B., Arden, Huang. (2007). On the optimal linear filtering techniques for noise reduction. Speech Communications, 49(2), 305-316.

[6] https://www.researchgate.net/publication/266648972_A_Noise_Reduction_Method_Based_on_LMS_Adaptiv e_Filter_of_Audio_Signals

[7] https://www.researchgate.net/publication/267774899_Implementation_of_the_LMS_Algorithm_for_Noise_Cancellation_on_Speech_Using_the_ ARM_LPC2378_Processor.

[8] https://en.wikipedia.org/wiki/Adaptive_filter

How to cite this paper

Amit Kukker, Yash Nigam, Tushar Sawle, Rajeet Kumar "Audio Quality Enhancement Using Adaptive Filters" Iconic Research And Engineering Journals Volume 6 Issue 1 2022 Page 165-169
Amit Kukker, Yash Nigam, Tushar Sawle, Rajeet Kumar "Audio Quality Enhancement Using Adaptive Filters" Iconic Research And Engineering Journals, vol. 6, no. 1, Jul. 2022
Amit Kukker, Yash Nigam, Tushar Sawle, Rajeet Kumar (2022). Audio Quality Enhancement Using Adaptive Filters. Iconic Research And Engineering Journals, 6(1).
Amit Kukker, Yash Nigam, Tushar Sawle, Rajeet Kumar "Audio Quality Enhancement Using Adaptive Filters" Iconic Research And Engineering Journals, vol. 6, no. 1, Jul. 2022.
@article{1703621,
      author = {Amit Kukker, Yash Nigam, Tushar Sawle, Rajeet Kumar},
      title = {Audio Quality Enhancement Using Adaptive Filters},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {6},
      number = {1},
      pages = {165-169},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1703621.pdf},
      abstract = {Audio quality enhancing plays a vital role in the field of speech recognition, communication, medical etc. The most widely used method is an optimal linear filtering that can reduce the noise level present in an audio signal and improve its signal to noise ratio (SNR). Here, we propose Adaptive LMS filtering method that can improve SNR and enhance audio quality in a very fruitful manner. The signal is filtered at once and the filter coefficients are computed adaptively in an exponential algorithm. The simulation results show a higher audio quality than the raw noise signal. Almost all practical signalling applications are difficult to implement. In this article, we propose a method to reduce noise in audio or speech signals using LMS adaptive filtering algorithms. The signal is filtered at once and the filter coefficients are computed adaptively in an exponential algorithm. The simulation results show a higher quality than the raw noise signal.},
      month = {July},
  }