Work place: Department of Computer Science and Engineering, UIE, Chandigarh University, Punjab, India
E-mail: abhishekkmr812@gmail.com
Website: https://orcid.org/0000-0003-4161-508X
Research Interests:
Biography
Abhishek Kumar is currently working as an Assistant director / professor in Computer science & Engineering Department in Chandigarh University, Punjab, India. He is Doctorate in computer science from University of Madras and he has done Post-Doctoral Fellow in Ingenium Research Group Ingenium Research Group Lab, Universidad De Castilla-La Mancha, Ciudad Real, and Ciudad Real Spain. He has done M.Tech in Computer Sci. & Engineering and B.Tech in I.T. from, Rajasthan Technical University, Kota India. He has total Academic teaching experience of more than 11 years along with 2 years teaching assistantship. He is having more than 100 publications in reputed, peer reviewed National and International Journals, books & Conferences. He is currently working as R&D Coordinator and Assistant Professor in Chitkara University Himachal Pradesh, India. He has guided more than 20 M.Tech Projects and Thesis and guiding 3 PhD Scholar. His research area includes- Artificial intelligence, Renewable Energy Image processing, Computer Vision, Data Mining, Machine Learning. He has been Session chair and keynote Speaker of many International conferences, webinars in India and Abroad. He has been the reviewer for IEEE and Inderscience Journal. He has authored/Co-Authored 6 books published internationally and edited 25 book (Published & ongoing with IET, Elsevier, Wiley, IGI GLOBAL Springer, Apple Academic Press, De-Gruyter and CRC etc. He has been member of various National and International professional societies in the field of engineering & research like Senior Member of IEEE , IAENG (International Association of Engineers), Associate Member of IRED (Institute of Research Engineers and Doctors).He is Patent holder and got Sir CV Raman National award for 2018 in young researcher and faculty Category from IJRP Group. He is acting as Series Editor for three books series, Quantum Computing with Degruyter Germany, Intelligent Energy with Elsevier, & Sustainable Energy with Nova, USA.
By Kruthika S. G Trisiladevi C Nagavi P. Mahesha Abhishek Kumar
DOI: https://doi.org/10.5815/ijigsp.2025.02.07, Pub. Date: 8 Apr. 2025
Forensic Voice Comparison (FVC) is a scientific analysis that examines audio recordings to determine whether they come from the same or different speakers in digital forensics. In this research work, the experiment utilizes three different techniques, like pre-processing, feature extraction, and classification. In preprocessing, the stationery noise reduction algorithm is used to remove unwanted background noise by increasing the clarity of the speech. This in turn helps to improve the overall audio quality by reducing distractions. Further, acoustic features like Mel Frequency Cepstral Coefficients (MFCC) are used to extract relevant and distinctive features from audio signals to characterize and analyze the unique vocal patterns of different individual. Later, the Generative Adversarial Network (GAN) is used to generate synthetic MFCC features and also for augmenting the data samples. Finally, the Logistic Regression (LR) is realized using UK framework for the classification of the model to predict whether the result is true or false. The results achieved in terms of accuracy are 62% considering 3899 samples and 85% when considering set of 985 samples for the Australian English datasets.
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