Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/8020
Title: Development of Non-Parametric Noise Reduction Algorithm for GSM Voice Signal
Authors: Gbadamosi, Safiu Abiodun
Aibinu, Musa Abiodun
Onumanyi, Adeiza James
Keywords: Voice signal; threshold value; GSM; Non-parametric; Standard deviation; Mean deviation.
Issue Date: Dec-2018
Publisher: ABUAD Journal of Engineering Research and Development (AJERD)
Citation: Gbadamosi, S. A., Aibinu, M. A., & Onumanyi, A. J. (2018). Development of Non-Parametric Noise Reduction Algorithm for GSM Voice Signal. Development, 1(3), 304-316.
Series/Report no.: Volume 1;
Abstract: Speech enhancement in Global System for Mobile communication (GSM) is an area of engineering that studies different kinds of techniques used in enhancing GSM voice signals. The presence of noise in GSM degrades the quality and intelligible of speech which impedes speaker identification and sound clarity. In this paper, a non-parametric noise reduction algorithm that incorporates an adaptive threshold technique is proposed to estimate the adaptive threshold value as a function of first and second-order statistics of the voice signal. It uses the cumulative value of minimum mean and maximum standard deviation value and minimum (mean and standard deviation) to minimize the effect of impairments introduced by background noise and GSM channels. The algorithm was implemented in a MATLAB environment. The results obtained indicate correlation coefficients of 53.93% and 45.52% for maximum and minimum threshold value at 2.95 standard deviations of noise and 77.93% and 75.83% for maximum and minimum threshold value at 0.25 standard deviation of the noise, respectively. Evaluation of the proposed algorithm was performed on real noisy voice signal and a correlation of 92.15% and 89.24% was achieved for both maximum and minimum threshold values with the mean square error of 0.0011% and 0.00033%, respectively. These results have proven the efficiency of the proposed algorithm. The threshold values have satisfied perfect noise reduction when the mean and standard deviation values are selected properly.
Description: Speech Processing
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/8020
ISSN: 2645-2685
Appears in Collections:Electrical/Electronic Engineering

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