Speaker Authentication pp 165-177 | Cite as
Randomly Prompted Speaker Verification
Chapter
First Online:
- 655 Downloads
Abstract
In today’s telecommunications environment, which includes wireless, landline, VoIP, and computer networks, the mismatch between training and testing environments poses a big challenge to speaker authentication systems. In Chapter 8, we addressed the mismatch problem from a feature extraction point of view. In this chapter, we address the problem from an acoustic modeling point of view. These two approaches can be used independently or jointly.
Keywords
Feature Vector Linear Discriminant Analysis Speaker Recognition Test Utterance Cohort Normalization
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Preview
Unable to display preview. Download preview PDF.
References
- 1.Chair, Z. Varshney, P.K.: Optimal data fusion in multiple sensor detection systems. IEEE Transactions on Aerospace and Electronic Systems AES-22 98–101 (1986)CrossRefGoogle Scholar
- 2.Duda, R.O., Hart, P.E., Pattern Classification and Scene Analysis. Wiley, New York (1973)zbMATHGoogle Scholar
- 3.Farell, K.R., Mammone, R.J., and Assaleh, K. T., Speaker recognition using neural networks and conventional classifiers, IEEE Transactions on Speech and Audio Processing, vol. 2, Part II, January 1994Google Scholar
- 4.Fisher, R.A.: The statistical utilization of multiple measurements. Annals of Eugenics 8, 376–386 (1938)CrossRefGoogle Scholar
- 5.Johnson, R.A., Wichern, D.W.: Applied Multivariate Statistical Analysis. Prentice Hall, New Jersey (1988)zbMATHGoogle Scholar
- 6.Lee, C.-H., Rabiner, L.R.: A frame-synchronous network search algorithm for connected word recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing 37, 1649–1658 (1989)CrossRefGoogle Scholar
- 7.Li, Q., Parthasarathy, S., Rosenberg, A. E., and Tufts, D. W., Normalized discriminant analysis with application to a hybrid speaker-verification system, in IEEE International Conference on Acoustics, Speech, and Signal Processing (Atlanta), May 1996Google Scholar
- 8.Li, Q. and Tufts, D. W., Improving discriminant neural network (DNN) design by the use of principal component analysis, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (Detroit, MI), pp. 3375–3379, May 1995Google Scholar
- 9.Li, Q. and Tufts, D.W., Synthesizing neural networks by sequential addition of hidden nodes, in Proceedings of the IEEE International Conference on Neural Networks (Orlando, FL), pp. 708–713, June 1994Google Scholar
- 10.Li, Q., Tufts, D. W., Duhaime, R., and August, P., Fast training algorithms for large data sets with application to classification of multispectral images, in Proceedings of the IEEE 28th Asilomar Conference (Pacific Grove), October 1994Google Scholar
- 11.Liou, H.S. and Mammone, R.J., A subword neural tree network approach to text-dependent speaker verification, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (Detroit, MI), pp. 357–360, May 1995Google Scholar
- 12.Liu, C.S., Lee, C.-H., Chou, W., Juang, B.-H., Rosenberg, A.E.: A study on minimum error discriminative training for speaker recognition. Journal of the Acoustical Society of America 97, 637–648 (1995)CrossRefGoogle Scholar
- 13.Netsch, L. P. and Doddington, G. R., Speaker verification using temporal decorrelation post-processing, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, 1992Google Scholar
- 14.Rosenberg, A. E. and DeLong, J., HMM-based speaker verification using a telephone network database of connected digital utterances, Technical Memorandum BL01126-931206-23TM, AT&T Bell Laboratories, December 1993Google Scholar
- 15.Rosenberg, A. E., DeLong, J., Lee, C.-H., Juang, B.-H., and Soong, F. K., The use of cohort normalized scores for speaker verification, in Proceedings of the International Conference on Spoken Language Processing (Banff, Alberta, Canada), pp. 599–602, October 1992Google Scholar
- 16.Setlur, A. R., Sukkar, R. A., and Gandhi, M. B., Speaker verification using mixture likelihood profiles extracted from speaker independent hidden Markov models, in Submitted to International Conference on Acoustics, Speech, and Signal Processing, 1996Google Scholar
- 17.Sukkar, R. A., Gandhi, M. B., and Setlur, A. R., Speaker verification using mixture decomposition discrimination, Technical Memorandum NQ8320300-950130-01TM, AT&T Bell Laboratories, January 1995Google Scholar
- 18.Tufts, D. W. and Li, Q., Principal feature classification, in Neural Networks for Signal Processing V, Proceedings of the 1995 IEEE Workshop (Cambridge, MA), August 1995Google Scholar
Copyright information
© Springer-Verlag Berlin Heidelberg 2012