Cancelable Speaker Identification Based on Inverse Filter | ||||
| Menoufia Journal of Electronic Engineering Research | ||||
| Article 46, Volume 28, ICEEM2019-Special Issue, 2019, Page 133-137 | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjeer.2019.76969 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Marwa Elsayed1; Walid El-Shafai 2; Mohsen A. Rashwan3; Moawad I. Dessouky4; Adel S. El-Fishawy4; Fathi E. Abd El-Samie5
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| 1Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University: Menouf, Egypt | ||||
| 2Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University: Menouf, Egypt | ||||
| 3Department of Electronics and Electrical Communications Engineering Faculty of Engineering Cairo University: Cairo , Egypt | ||||
| 4Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University: Menouf, Egypt | ||||
| 5Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University: Menouf, Egypt | ||||
| Abstract | ||||
| Nowadays, biometric systems have replaced the password or token based authentication systems in many fields to improve the security level. Biometric authentication systems automatically identify or verify a person using physical, biological, and behavioral characteristics. Unfortunately, these systems have suffered from hacking trials. This paper presents masking techniques for cancelable speaker identification. The basic concept is to use another version of the original speaker signal created through a masking techniques to keep the original signals safe and away from utilization in the system. The basic idea is adding some sort of noise to the speech signal and magnification of this noise by the proposed techniques. The proposed techniques are discrete wavelet transform (DWT), wavelet thresholding, Linear Minimum Mean Square Error (LMMSE) technique and invers filter. A comparison between these techniques is established using objective quality measures of speaker identification. Simulation results show good performance of the technique based on invers filter. | ||||
| Keywords | ||||
| Speaker identification; biometric systems; Cancelable Biometric; LMMSE; invers filter | ||||
| References | ||||
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