Research Article
Year 2023,
Volume: 07 Issue: 2, 17 - 22, 23.12.2023
Abstract
Biometric authentication systems reveal individuals' physical or behavioral uniqueness and identify them by comparing them with existing records. Today, many biometric recognition systems, such as fingerprint reading, palm reading, and face reading, are being studied and used. The human voice is also among the techniques used for this purpose. Due to this feature, the human voice performs secure transactions and authentication in various fields. Based on these voice features, we used a dataset of 66,569 voice recordings. The voice recordings were revised to include six sentences of at least six words each from 24 different people to get the maximum benefit from the dataset. The voices in the reduced dataset were labeled as sentences belonging to the same person and sentences belonging to different people and converted into matrix form. A biometric recognition study resulted in a correlation score of 0.88. As a result of these processes, the feasibility of a voice biometric recognition system with artificial intelligence has been demonstrated.
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Year 2023,
Volume: 07 Issue: 2, 17 - 22, 23.12.2023
Abstract
References
- M. Nizam Kamarudin, H. Nizam Mohd Shah, M. Zamzuri Ab Rashid, M. Fairus Abdollah, C. Kok Lin, and Z. Kamis, “Biometric Voice Recognition in Security System,” 2014, Accessed: Aug. 28, 2023.
- K. Fatima, S. Nawaz, and S. Mehrban, “Biometric Authentication in Health Care Sector: A Survey,” 3rd International Conference on Innovative Computing, ICIC 2019, Nov. 2019, doi: 10.1109/ICIC48496.2019.8966699.C. Berghoff, M. Neu, and A. von Twickel, “The Interplay of AI and Biometrics: Challenges and Opportunities,” Computer (Long Beach Calif), vol. 54, no. 09, pp. 80–85, Sep. 2021, doi: 10.1109/MC.2021.3084656.
- C. Berghoff, M. Neu, and A. von Twickel, “Vulnerabilities of Connectionist AI Applications: Evaluation and Defense,” Front Big Data, vol. 3, p. 544373, Jul. 2020, doi: 10.3389/FDATA.2020.00023/BIBTEXA. Boles and P. Rad, “Voice Biometrics: Deep Learning-based Voiceprint Authentication System,” 2017, doi: 10.1109/SYSOSE.2017.7994971.
- S. Albalawi, L. Alshahrani, N. Albalawi, R. Kilabi, and A. Alhakamy, “A Comprehensive Overview on Biometric Authentication Systems using Artificial Intelligence Techniques,” International Journal of Advanced Computer Science and Applications, vol. 13, no. 4, pp. 782– 791, 2022, doi: 10.14569/IJACSA.2022.0130491.
- J. Noyes and C. Frankish, “Speech recognition technology for individuals with disabilities,” Augmentative and Alternative Communication, vol. 8, no. 4, pp. 297–303, 1992.
- F. Alcantud, I. Dolz, C. Gaya, and M. Martín, “The voice recognition system as a way of accessing the computer for people with physical standards as usual,” Technol Disabil, vol. 18, no. 3, pp. 89–97, 2006, doi: 10.3233/TAD-2006- 18301.
- A. Boles and P. Rad, “Voice biometrics: Deep learning-based voiceprint authentication system,” 2017 12th System of Systems Engineering Conference, SoSE 2017, Jul. 2017, doi: 10.1109/SYSOSE.2017.7994971.
- H. H. Zhu, Q. H. He, H. Tang, and W. H. Cao, “Voiceprint-biometric template design and authentication based on cloud computing security,” 2011 International Conference on Cloud and Service Computing, pp. 302–308, 2011, doi: 10.1109/CSC.2011.6138538.
- "Common Voice.” https://commonvoice.mozilla.org/en/datasets (accessed Dec. 20, 2022).
- H. Shahid, S. Aziz, A. Aymin, M. U. Khan, and A. N. Remete, “A Survey on AI-based ECG, PPG, and PCG Signals Based Biometric Authentication System; A Survey on AI-based ECG, PPG, and PCG Signals Based Biometric Authentication System,” 2021, doi: 10.1109/ICECube53880.2021.9628307.
- C. Berghoff, M. Neu, and A. von Twickel, “Vulnerabilities of Connectionist AI Applications: Evaluation and Defense,” Front Big Data, vol. 3, p. 23, Jul. 2020, doi: 10.3389/FDATA.2020.00023/BIBTEX.
- S. B. Sadkhan, B. K. Al-Shukur, and A. K. Mattar, “Biometric voice authentication autoevaluation system,” 2017 Annual Conference on New Trends in Information and Communications Technology Applications, NTICT 2017, pp. 174– 179, Jul. 2017, doi: 10.1109/NTICT.2017.7976100.
- S. B. Sadkhan, B. K. Al-Shukur, and A. K. Mattar, “Biometric voice authentication autoevaluation system,” 2017 Annual Conference on New Trends in Information and Communications Technology Applications, NTICT 2017, pp. 174– 179, Jul. 2017, doi: 10.1109/NTICT.2017.7976100.
- J. Gałka, M. Masior and M. Salasa, "Voice authentication embedded solution for secured access control," in IEEE Transactions on Consumer Electronics, vol. 60, no. 4, pp. 653-661, Nov. 2014, doi: 10.1109/TCE.2014.7027339.
There are 14 citations in total.
Details
| Primary Language | English |
|---|---|
| Subjects | Mathematical Sciences |
| Journal Section | Articles |
| Authors | |
| Early Pub Date | December 18, 2023 |
| Publication Date | December 23, 2023 |
| Submission Date | March 4, 2023 |
| Acceptance Date | December 17, 2023 |
| Published in Issue | Year 2023 Volume: 07 Issue: 2 |
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