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

The main intention of this research work is to extract the actual words from stammering signals. Materials and Methods: Novel stammering voice detection in Wiener filter (N = 10) and Median filter (N = 10) were iterated to improve the voice for the voice stammering. Sample size is calculated using Gpower with 89% and threshold 0.05 for two groups. Results: Wiener filter has notably better accuracy percentage (91.0%) compared to Median Filter accuracy (81.9%) with significance value of 0.038 (p<0.05). Conclusion: The accuracy of the Wiener filter is better when compared to the accuracy of Median filter.