Abstract
In this paper we present a new speaker recognition system based on the fusion of two identification classifiers followed by a verification step. The user pronounces two passwords: the first one is composed by three words uniquely combined from a set of 21 possible words, while the second password represents the name of the user. The first step of the proposed system uses the first password to feed two identification classifiers: a speaker identification system (text independent) and a isolated word identification system (speaker independent). The isolated word identification system is constructed as the fusion of three classifiers, one for each word of the first password. The aim of this first step is to identify a couple speaker/password corresponding to the first password by combining the results of the two identification classifiers. A verification system is then applied on the second password in order to confirm or infirm the identification result (speaker identity) given by the fusion above. Compared with a state of the art speaker recognition system (text dependent) that gives an EER of 4.76%, the first step of the proposed system provides an EER of 0.38%, while the second step an EER of 0.26% for a text independent verification and of 0.13% for a text dependent verification.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Atkins, W.: A testing time for face recognition technology. Biometric Technology Today 147, 195–197 (2001)
BenZeghiba, M., Bourlard, H.: User-customized password speaker verification using multiple reference and background models. Speech Communication 8, 1200–1213 (2006)
Bimbot, F., Bonastre, J.-F., Fredouille, C., Gravier, G., Chagnolleau, I., Meignier, S., Merlin, T., Garciya, J., Delacrtaz, D., Reynolds, D.: A tutorial on text-independent speaker verification. EURASIP Journal on Applied Signal Processing 4, 430–451 (2004)
Bonastre, J.-F., Wils, F., Meignier, S.: Alize, a free toolkit for speaker recognition. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 737–740 (2005)
Doddington, G.: Speaker recognition identifying people by their voices. In: Proc. of the IEEE, vol. 73, pp. 1651–1664 (1985)
Furui, S.: Recent advances in speaker recognition. In: Bigün, J., Borgefors, G., Chollet, G. (eds.) AVBPA 1997. LNCS, vol. 1206, pp. 237–252. Springer, Heidelberg (1997)
Gauvain, J.-L., Lee, C.-H.: Maximum a posteriori estimation for multivariate gaussian mixture observations of markov chains. IEEE Trans. on Speech and Audio 2, 291–298 (1994)
Higgins, J.E., Damper, R.I., Harris, C.J.: Information fusion for subband-hmm speaker recognition. In: International Joint Conference on Neural Networks, vol. 2, pp. 1504–1509
Kinnunen, T.: Spectral Features for Automatic Text-Independent Speaker Recognition, PhDThesis, University of Joensuu, Finland (2003)
Kinnunen, T., Hautamki, V., Franti, P.: Fusion of spectral feature sets for accurate speaker identification. In: 9th International Conference Speech and Computer (SPECOM), pp. 361–365 (2004)
Lee, C.H., Soong, F., Paliwal, K.: Automatic Speech and Speaker Recognition. Springer, London (1996)
Reynolds, D.: Speaker identification and verification using gaussian mixture speaker models. Speech Communication 17, 91–108 (1995)
Sigurdsson, S., Petersen, K.B., Lehn-Schiøler, T.: Mel frequency cepstral coeficients: An evaluation of robustness of mp3 encoded music. In: Proceedings of the Seventh International Conference on Music Information Retrieval (ISMIR), pp. 286–289 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chenafa, M., Istrate, D., Vrabie, V., Herbin, M. (2008). Biometric System Based on Voice Recognition Using Multiclassifiers. In: Schouten, B., Juul, N.C., Drygajlo, A., Tistarelli, M. (eds) Biometrics and Identity Management. BioID 2008. Lecture Notes in Computer Science, vol 5372. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89991-4_22
Download citation
DOI: https://doi.org/10.1007/978-3-540-89991-4_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89990-7
Online ISBN: 978-3-540-89991-4
eBook Packages: Computer ScienceComputer Science (R0)