Intelligent Speaker Verification based Biometric System for Electronic Commerce Applications
Electronic commerce is growing rapidly with on-line
sales already heading for hundreds of billion dollars per year. Due to
the huge amount of money transferred everyday, an increased
security level is required. In this work we present the architecture of
an intelligent speaker verification system, which is able to accurately
verify the registered users of an e-commerce service using only their
voices as an input. According to the proposed architecture, a
transaction-based e-commerce application should be complemented
by a biometric server where customer-s unique set of speech models
(voiceprint) is stored. The verification procedure requests from the
user to pronounce a personalized sequence of digits and after
capturing speech and extracting voice features at the client side are
sent back to the biometric server. The biometric server uses pattern
recognition to decide whether the received features match the stored
voiceprint of the customer who claims to be, and accordingly grants
verification. The proposed architecture can provide e-commerce
applications with a higher degree of certainty regarding the identity
of a customer, and prevent impostors to execute fraudulent
transactions.
[1] A. J. Harris and D. C. Yen, Biometric authentication: assuring access to
information, Information Management & Security 10/1, pp. 12-19, 2002.
[2] J.L. Dugelay, J.C. Junqua, C. Kotropoulos, and R. Kuhn, Recent
Advantages in Biometric Person Authentication, ICASSP 2002,
International Conference on Acoustics, Speech and Signal Processing,
May 13, 2002, Orlando, Florida, USA.
[3] J. Ashbourn, Biometrics: advanced identity verification: The complete
guide, Springer-Verlag, London, 2000.
[4] A. Klosterman and G. Ganger, Secure continuous biometric-enhanced
authentication, Carnegie Mellon University, Pittsburgh, PA.
[5] L. R. Rabiner, A Tutorial on Hidden Markov Models and selected
applications in Speech Recognition, Proc. IEEE, vol. 77, pp. 257-286,
Feb. 1989.
[6] R. J. Mammone, X. Zhang and R. P. Ramachandran, Robust Speaker
Recognition, A Feature-Based Approach, IEEE Signal Processing
Magazine, 13 (5), September 1996, 55-71.
[7] J. P. Campbell, Speaker Recognition: A Tutorial, Proceedings of the
IEEE, 85(9), September 1997, 1437-1462.
[8] L. Rabiner, BH Juang, Fundamentals of Speech Recognition, (Prentice
Hall, 1993).
[9] S. Furui, Cepstral Analysis technique for automatic speaker verification,
IEEE Transactions on Acoustics, Speech and Signal Processing, vol.
ASSP-29, 1981.
[10] J.R. Deller, J.G.Proakis, and J.H.L.Hansen, Discrete-Time Processing of
Speech Signals, Macmillan 1993.
[11] D. Reynolds, Speaker Identification and Verification using Gaussian
Mixture speaker models, Speech Communications, vol 17, pp. 91-108,
1995.
[12] S. Navanati, M. Thieme, and R. Navanati, Biometrics: Identify
verification in a networked world (John Wiley & Sons, Inc. 2002.
[13] Hynek Hermansky, Exploring Temporal Domain for Robustness in
Speech Recognition, 15th International Congress on Acoustics, 1995.
[1] A. J. Harris and D. C. Yen, Biometric authentication: assuring access to
information, Information Management & Security 10/1, pp. 12-19, 2002.
[2] J.L. Dugelay, J.C. Junqua, C. Kotropoulos, and R. Kuhn, Recent
Advantages in Biometric Person Authentication, ICASSP 2002,
International Conference on Acoustics, Speech and Signal Processing,
May 13, 2002, Orlando, Florida, USA.
[3] J. Ashbourn, Biometrics: advanced identity verification: The complete
guide, Springer-Verlag, London, 2000.
[4] A. Klosterman and G. Ganger, Secure continuous biometric-enhanced
authentication, Carnegie Mellon University, Pittsburgh, PA.
[5] L. R. Rabiner, A Tutorial on Hidden Markov Models and selected
applications in Speech Recognition, Proc. IEEE, vol. 77, pp. 257-286,
Feb. 1989.
[6] R. J. Mammone, X. Zhang and R. P. Ramachandran, Robust Speaker
Recognition, A Feature-Based Approach, IEEE Signal Processing
Magazine, 13 (5), September 1996, 55-71.
[7] J. P. Campbell, Speaker Recognition: A Tutorial, Proceedings of the
IEEE, 85(9), September 1997, 1437-1462.
[8] L. Rabiner, BH Juang, Fundamentals of Speech Recognition, (Prentice
Hall, 1993).
[9] S. Furui, Cepstral Analysis technique for automatic speaker verification,
IEEE Transactions on Acoustics, Speech and Signal Processing, vol.
ASSP-29, 1981.
[10] J.R. Deller, J.G.Proakis, and J.H.L.Hansen, Discrete-Time Processing of
Speech Signals, Macmillan 1993.
[11] D. Reynolds, Speaker Identification and Verification using Gaussian
Mixture speaker models, Speech Communications, vol 17, pp. 91-108,
1995.
[12] S. Navanati, M. Thieme, and R. Navanati, Biometrics: Identify
verification in a networked world (John Wiley & Sons, Inc. 2002.
[13] Hynek Hermansky, Exploring Temporal Domain for Robustness in
Speech Recognition, 15th International Congress on Acoustics, 1995.
@article{"International Journal of Business, Human and Social Sciences:50428", author = "Anastasis Kounoudes and Stephanos Mavromoustakos", title = "Intelligent Speaker Verification based Biometric System for Electronic Commerce Applications", abstract = "Electronic commerce is growing rapidly with on-line
sales already heading for hundreds of billion dollars per year. Due to
the huge amount of money transferred everyday, an increased
security level is required. In this work we present the architecture of
an intelligent speaker verification system, which is able to accurately
verify the registered users of an e-commerce service using only their
voices as an input. According to the proposed architecture, a
transaction-based e-commerce application should be complemented
by a biometric server where customer-s unique set of speech models
(voiceprint) is stored. The verification procedure requests from the
user to pronounce a personalized sequence of digits and after
capturing speech and extracting voice features at the client side are
sent back to the biometric server. The biometric server uses pattern
recognition to decide whether the received features match the stored
voiceprint of the customer who claims to be, and accordingly grants
verification. The proposed architecture can provide e-commerce
applications with a higher degree of certainty regarding the identity
of a customer, and prevent impostors to execute fraudulent
transactions.", keywords = "Speaker Recognition, Biometrics, E-commercesecurity.", volume = "2", number = "8", pages = "811-5", }