Comparative Performance Analysis for Maximum Segmented Accuracy in Voice Stammer using Wiener Filter and Gaussian Filter Recognition

By deciphering the stammering signals, the researchers hope to determine what the speaker is actually saying. The performance analysis for the highest segmental accuracy of the voice stutter made use of the Wiener filter with a N value of ten in place of the Gaussian filter recognition, which gets rid of the noise. Utilizing filters is one way to do classification. The Gpower test that is being used is approximately 80%. The Wiener filter, which has a success rate of 91.0%, is superior to the Gaussian filter, which has a success rate of 75.5% and a significance level of 0.039 (two-tailed, p 0.05). The Wiener filter can remove noise from an input signal more accurately. When compared to the accuracy of the Gaussian filter, the accuracy of the Wiener filter is significantly higher.