Noise Reduction and Echo Cancellation Using Threshold Filters in Hands Free Communication Systems

摘要

Background noise, far-end acoustic echo, and room reverberation dramatically degrade the performance of many hands-free speech communication systems, in practical environments. For example, for automatic speech recognition system, noises result in the mismatch between the training and testing conditions, further degrading the performance of recognition system in real-world conditions. The threshold filtering can be executed with the help of mask windows of different sizes. For this, first we have to detect the noisy pixel, if the detected pixel is contaminated it can be identified by the homogeneity level of the local region around that pixel. Suppose the signal is corrupted by noise, which means the pixel value, is both 0 and 255 then we must calculate the threshold value and compare it with the neighbouring upper and lower pixels and find out which of them is homogeneous with the threshold value and replace the pixel with that value..............