Almomani, A, Gupta, B B, Alomoush, W, Abdalla, Meral, Hamad, Ghufran, Abbass, Anwar, Jabai, Aseel, Alauthman, Mohammad and Alweshah, Mohammed (2023) Age and Gender Classification Using Backpropagation and Bagging Algorithms. Computers, Materials and Continua, 74 (2). pp. 3045-3062. ISSN 1546-2218
Full text not available from this repository.Abstract
Voice classification is important in creating more intelligent systems that help with student exams, identifying criminals, and security systems. The main aim of the research is to develop a system able to predicate and classify gender, age, and accent. So, a new system called Classifying Voice Gender, Age, and Accent (CVGAA) is proposed. Backpropagation and bagging algorithms are designed to improve voice recognition systems that incorporate sensory voice features such as rhythm-based features used to train the device to distinguish between the two gender categories. It has high precision compared to other algorithms used in this problem, as the adaptive backpropagation algorithm had an accuracy of 98% and the Bagging algorithm had an accuracy of 98.10% in the gender identification data. Bagging has the best accuracy among all algorithms, with 55.39% accuracy in the voice common dataset and age classification and accent accuracy in a speech accent of 78.94%. © 2023 Tech Science Press. All rights reserved.
Affiliation: | Skyline University College |
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SUC Author(s): | Almomani, A ORCID: https://orcid.org/0000-0002-8808-6114, Gupta, B B and Alomoush, W ORCID: https://orcid.org/0000-0002-2937-4327 |
All Author(s): | Almomani, A, Gupta, B B, Alomoush, W, Abdalla, Meral, Hamad, Ghufran, Abbass, Anwar, Jabai, Aseel, Alauthman, Mohammad and Alweshah, Mohammed |
Item Type: | Article |
Uncontrolled Keywords: | accent, age, AI classifiers, back propagation algorithms, bagging algorithms, Classify voice gender |
Subjects: | B Information Technology > BM Artificial Intelligence |
Divisions: | Skyline University College > School of IT |
Depositing User: | Mr Mosys Team |
Date Deposited: | 25 Dec 2023 13:57 |
Last Modified: | 25 Dec 2023 13:57 |
URI: | https://research.skylineuniversity.ac.ae/id/eprint/610 |
Publisher URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.... |
Publisher OA policy: | https://v2.sherpa.ac.uk/cgi/search/publication/bas... |
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