Spoken Signature For User Authentication
| Type of publication: | Article |
| Citation: | humm08:spie |
| Journal: | SPIE Journal of Electronic Imaging, Special Section on Biometrics: ASUI January-March 2008 |
| Volume: | 17 |
| Number: | 1 |
| Year: | 2008 |
| Month: | April |
| Pages: | 011013-1--011013-11 |
| URL: | http://www.hennebert.org/downl... |
| DOI: | doi:10.1117/1.2898526 |
| Abstract: | We are proposing a new user authentication system based on spoken signatures where online signature and speech signals are acquired simultaneously. The main benefit of this multimodal approach is a better accuracy at no extra costs for the user in terms of access time or inconvenience. Another benefit lies in a better robustness against intentional forgeries due to the extra difficulty for the forger to produce both signals. We have set up an experimental framework to measure these benefits on MyIDea, a realistic multimodal biometric database publicly available. More specifically, we evaluate the performance of state-of-the-art modelling systems based on GMM and HMM applied independently to the pen and voice signal where a simple rule-based score fusion procedure is used. We conclude that the best performance is achieved by the HMMs, provided that their topology is optimized on a per user basis. Furthermore, we show that more precise models can be obtained through the use of Maximum a posteriori probability (MAP) training instead of the classically used Expectation Maximization (EM). We also measure the impact of multi-session scenarios versus mono-session scenarios and the impact of skilled versus unskilled signature forgeries attacks. |
| Keywords: | Biometrics, Signature Verification, Speaker Verification |
| Authors | |
| Added by: | [] |
| Total mark: | 0 |
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