Reduction Gaussian Noise of Speech Sound Signals Using Technical Mean Digital filter Traditional and Enhanced


Many techniques concerning processes of verbal audio signal were examined aiming to eliminate noise, amelioration and analysis. Imitation for Collective Gaussian Noise using a computer software for different situations of standard deviation of noise (g =1,2 ….10) and with zero average. This noise was added collectively to verbal signal components, audio signals impure with noise were processed by using mean filter and statistical properties of signals resulted from process in order to determine the quality of signal and filter efficiency. Notably, process leads to lose some significant features of audio signal. Therefore, filter was ameliorated by adding some additional conditions to the components under process in order to keep the significant features of signal. Audio signals impure with noise were processed by using the ameliorated Mean filter and then examining the statistical properties resulted from process. Ameliorated version of Mean filter made good results in improving signal impure with noise. Changes on pure signals were examined through statistical standard i.e. [Mean µ, standard deviation, Mean Square Error MSE] of impure, pure and ameliorated signals. Great amelioration was noticed in these characteristics along with keeping significant and distinguishing features of audio signal.