Perdana, Novario J. and Herwindiati, Dyah E. and Sarmin, Nor H. (2022) Voice recognition system for user authentication using Gaussian mixture model. In: 4th IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2022, 13 September 2022 - 15 September 2022, Kota Kinabalu, Sabah, Malaysia.
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Official URL: http://dx.doi.org/10.1109/IICAIET55139.2022.993685...
Abstract
The use of biometrics in the user authentication process is the leading choice today. One of the biometrics that can be used is the human voice. In this paper, a voice authentication system using the Gaussian Mixture Model (GMM) is proposed. GMM was chosen because of the ease and accuracy in classifying the data. Voice data features are extracted using Linear Predictive Coding (LPC) before being classified using GMM. Voice data was recorded directly from 30 respondents using laptops and smartphones. Additional devices in the form of earphones were added to get better results. The system's learning process has an accuracy of 84%, and the overall testing process has an accuracy of 82 %. There are also differences in the accuracy of user authentication between data that use enhancements and those that do not. They are 87% and 72 %, respectively.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | biometrics, user authentication, voice |
| Subjects: | Q Science > Q Science (General) |
| Divisions: | Science |
| ID Code: | 98794 |
| Deposited By: | Yanti Mohd Shah |
| Deposited On: | 02 Feb 2023 08:54 |
| Last Modified: | 02 Feb 2023 08:54 |
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