7d13987c195caa108f5-338e 20250325121745595 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Innovative Technology and Exploring Engineering IJITEE 22783075 10.35940/ijitee https://www.ijitee.org/ 03 30 2025 14 4 Department of Computer Science, Babcock University, Ilishan Remo (Ogun State), Nigeria. Alimi Sheriff https://orcid.org/0009-0002-1954-1598 Yussuff I. O. Abayomi https://orcid.org/0000-0003-3829-9944 Associate Professor, Department of Electronic and Computer Engineering, Lagos State University, Epe (Lagos), Nigeria. Voice activity detection (VAD) separates speech segments from silent segments of an audio signal, and it is valuable for many speech-processing applications because it assists in improving performance and system efficiency; such applications include speech recognition and speaker verification. In this study, K-means, a clustering algorithm, was extended to a thresholding algorithm termed K-means weighted thresholding and was utilized for discriminating voiced/speech segments from silent segments from audio or speech signals. The voice signal was fragmented into frames of 2048 samples, and the spectral power of the frames served as input for computing the threshold value by the extended k-means algorithm; hence, any frame whose spectral power is greater than or equal to the threshold value is considered to part of the voice segments; otherwise, it is tagged as a silent frame. The implemented voice activity detection system achieved outstanding performances with a true acceptance rate (sensitivity), false acceptance rate, true rejection rate (specificity), false rejection rate (miss rate), and a classification accuracy of 100%, 0.025%, 100%, 0%, and 99.97%, respectively. 03 30 2025 03 30 2025 1 7 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true International Journal of Innovative Technology and Exploring Engineering (IJITEE) Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) Based on my understanding, this article has no conflicts of interest. This article has not been sponsored or funded by any organization or agency. The independence of this research is a crucial factor in affirming its impartiality, as it has been conducted without any external sway. The data provided in this article is exempt from the requirement for ethical approval or participant consent. The adequate resources of this article are publicly accessible. The authorship of this article is contributed equally to all participating individuals. 10.35940/ijitee.D1051.14040325 https://www.ijitee.org/portfolio-item/D105114040325/