Identification of Drug-addicted People using Short Length of Voice Signal through Haar and Symlet Wavelet Transform

Identification of Drug-addicted People using Short Length of Voice Signal through Haar and Symlet Wavelet Transform

Sadia Afrin^1*, Md. Sajeebul Islam Sk.², Md. Kazi Nazmul Islam³ and Md. Rafiqul Islam⁴

¹Department of Basic Science, Primeasia University, Dhaka, Bangladesh

^2,3,4Mathematics Discipline, Khulna University, Khulna, Bangladesh

Publication Information

Journal Title: International Journal of Research and Scientific Innovation (IJRSI)
Author(s):Afrin, Sadia; Sk, Md. Sajeebul Islam ;Islam, Md. Kazi Nazmul ;Islam, Md. Rafiqul
Published On: 08/022025
Volume: 12
Issue: 5
First Page:19
Last Page:25
ISSN: 2321-2705

Cite this Article Afrin, Sadia; Sk, Md. Sajeebul Islam ;Islam, Md. Kazi Nazmul ;Islam, Md. Rafiqul  ; Identification of Drug-addicted People using Short Length of Voice Signal through Haar and Symlet Wavelet Transform, Volume 12 Issue 5, International Journal of Research and Scientific Innovation (IJRSI), 19-25, Published on 08/02/2025, Available at https://rsisinternational.org/journals/ijrsi/articles/identification-of-drug-addicted-people-using-short-length-of-voice-signal-through-haar-and-symlet-wavelet-transform/

Abstract

Recognizing and classifying signals is one of the most significant tasks nowadays. For an uncountable number of purposes, classification, pattern recognition, data pre-processing, and prediction science are used worldwide. In this work, our objective is to understand, analyze, visualize, recognize, and identify drug-addicted and non-addicted people by using their short length of voice signals through Haar and Symlet (Sym2) wavelet transform. Here, we used signals of speech at a considerable length to achieve our goal and provide opportunities for the law-and-order enforcing authority and the people who are interested in this area. We visualize each signal and analyze them using different wavelet transform to understand the similarities and dissimilarities between the voice signals. After wavelet transform, we calculate the PSNR and SNR values of the voice signals using MATLAB wavelet toolbox. To the PSNR and SNR values of the voice signals and try to make the similarities and dissimilarities between the voice signals. From the values we can make a decision to identifying a Drug-addicted people.

Keywords: Drug-addicted people detection, wavelet transform, power spectrum, signal to noise ratio (SNR), peak signal to noise ratio (PSNR)