Windowed Adaptive Filtering for Reducing Noise in Audio Signals during Transmission to Remote Locations

Abstract

Audio signals are so important to mankind nowadays that they are now carried over transmission lines to remote ends for entertainment purposes or to send messages across and other purposes. Incidentally these audio signals can be contaminated either at the source or along this transmission lines by unwanted signals such as Additive White Gaussian Noise (AWGN), Random Noise, power line noise and other noise signals. To preserve the integrity of the audio signals at the receiving end, any noise contaminating the signal must be reduced to the barest minimum. In this paper a finite impulse response filter based on LMS algorithm is developed to remove AWGN from audio signals. During the adaptation process of the filter, every updated coefficient sequence is modified with Blackman-Harris window before being applied to the noisy audio. After design the optimum sampling parameters of the filter are determined to be sampling frequency of 8000Hz, filter order of 29 and step size of 0.006. An audio signal is generated by loading the Hallelujah song in the M-file of matlab into work space. An AWGN is generated with the matlab and added to the generated audio signal to form a noisy or contaminated audio signal. When the noisy signal is applied to the designed filter result shows that the noise in the signal drastically reduced to give a clean audio signal. Listening to the uncontaminated, contaminated and filtered audio signals and comparing them confirms the effectiveness of the adaptive filter in audio signal processing.