Comparative Performance Analysis of Music Audio Denoising Using Wavelet Technique

10 Pages Posted: 30 Nov 2020

See all articles by Pratik Jadhav

Pratik Jadhav

RamraoAdik Institute of Technology

Gargi Phadke

RamraoAdik Institute of Technology

Shamal Salunkhe

RamraoAdik Institute of Technology

Date Written: November 23, 2020

Abstract

Mostly communication channels are experiencing noises and it is very difficult to recover from the original signals without any noise. Denoising can be performed with various filtering techniques that can be separate the noise signal from the original signal. Filtering techniques have been proposed for noise removal from the digital musical signals. The overall performance of the filtering technique is less effective. Denoising of an audio signal is an area under development. In this article, music signals are considered input signals. Denoising techniques are compared based on different filter design techniques. A technique of filtering of noise is implemented and compared using Signal-to-Noise Ratio (SNR). Here for comparison, the Butterworth filter and different types of wavelet filters are used for denoising the musical signals. Daubechies wavelet techniques work better than existing methods is proven by SNR.

Keywords: Signal-to-Noise Ratio (SNR), Butterworth filter, Haar wavelet, Mean Squared Error (MSE)

Suggested Citation

Jadhav, Pratik and Phadke, Gargi and Salunkhe, Shamal, Comparative Performance Analysis of Music Audio Denoising Using Wavelet Technique (November 23, 2020). Proceedings of the 2nd International Conference on IoT, Social, Mobile, Analytics & Cloud in Computational Vision & Bio-Engineering (ISMAC-CVB 2020), Available at SSRN: https://ssrn.com/abstract=3735916 or http://dx.doi.org/10.2139/ssrn.3735916

Pratik Jadhav (Contact Author)

RamraoAdik Institute of Technology ( email )

Gargi Phadke

RamraoAdik Institute of Technology ( email )

Shamal Salunkhe

RamraoAdik Institute of Technology ( email )

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