Verbal Information Verification

  • Qi (Peter) LiEmail author
Part of the Signals and Communication Technology book series (SCT)


In this book, we have introduced various speaker authentication techniques. Each of the techniques can be considered as a technical component, such as speaker identification, speaker verification, verbal information verification, and so on. In real-world applications, a speaker authentication system can be designed by combining the technical components to construct a useful and convenient system to meet the requirements of a particular application. In this chapter we provide an example of a speaker authentication system design. Following this example, the author hopes readers can design their own system for their particular applications to improve the security level of the protected system. This design example was originally reported in [2].


Automatic Speech Recognition Verbal Information Speaker Recognition False Acceptance Rate False Rejection Rate 
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.


  1. 1.
    Anderson, T.W.: An introduction to multivariate statistical analysis, second edn. Wiley, New York (1984)Google Scholar
  2. 2.
    Kawahara, T., Lee, C.-H., and Juang, B.-H., Combining key-phrase detection and subword-based verification for flexible speech understanding, in Proceedings of ICASSP (Munich), pp. 1159–1162, May 1997Google Scholar
  3. 3.
    Lee, C.-H., Juang, B.-H., Chou, W., and Molina-Perez, J. J., A study on task- independent subword selection and modeling for speech recognition, in Proc. of ICSLP (Philadelphia), pp. 1816–1819, Oct. 1996Google Scholar
  4. 4.
    Li, Q. and Juang, B.-H., Speaker verification using verbal information veri- fication for automatic enrollment, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (Seattle), May 1998Google Scholar
  5. 5.
    Li, Q., Juang, B.-H., Zhou, Q., Lee, C.-H.: Automatic verbal informa- tion verification for user authentication. IEEE Trans. on Speech and Audio Processing 8, 585–596 (2000)CrossRefGoogle Scholar
  6. 6.
    Li, Q., Juang, B.-H., Zhou, Q., and Lee, C.-H., Verbal information verification, in Proceedings of EUROSPEECH (Rhode, Greece), pp. 839–842, Sept. 22-25 (1997)Google Scholar
  7. 7.
    Li, Q., Parthasarathy, S., and Rosenberg, A. E., A fast algorithm for stochastic matching with application to robust speaker verification, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (Munich), pp. 1543–1547, April 1997Google Scholar
  8. 8.
    Lleida, E. and Rose, R. C., Efficient decoding and training procedures for utterance verification in continuous speech recognition, in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing (Atlanta), pp. 507–510, May 1996Google Scholar
  9. 9.
    Neyman, J., Pearson, E.S.: On the problem of the most efficient tests of statistical hypotheses. Phil. Trans. Roy. Soc. A 231, 289–337 (1933)CrossRefGoogle Scholar
  10. 10.
    Neyman, J. and Pearson, E. S., On the use and interpretation of certain test criteria for purpose of statistical inference, Biometrika, vol. 20A, pp. Pt I, 175–240; Pt II, 1928Google Scholar
  11. 11.
    Parthasarathy, S. and Rosenberg, A. E., General phrase speaker verification using sub-word background models and likelihood-ratio scoring, in Proceedings of ICSLP-96 (Philadelphia), October 1996.Google Scholar
  12. 12.
    Rabiner, L. Juang B.-H.: Fundamentals of speech recognition. Englewood Cliffs, PTR Prentice Hall, NJ (1993)Google Scholar
  13. 13.
    Rahim, M. G., Lee, C.-H., and Juang, B.-H., Robust utterance verification for connected digits recognition, in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing, (Detroit), pp. 285–288, May 1995.Google Scholar
  14. 14.
    Rahim, M. G., Lee, C.-H., Juang, B.-H., and Chou, W., Discriminative ut- terance verification using minimum string verification error (MSVE) training, in Proc. IEEE Int. Conf. Acoustic, Speech, Signal Processing, (Atlanta), pp. 3585–3588, May 1996.Google Scholar
  15. 15.
    Rosenberg, A. E. and Parthasarathy, S., Speaker background models for con- nected digit password speaker verification, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, (Atlanta), pp. 8–84, May 1996.Google Scholar
  16. 16.
    Setlur, A. R., Sukkar, R. A., and Jacob, J., Correcting recognition errors via discriminative utterance verification, in Proc. Int. Conf. on Spoken Language Processing, (Philadelphia), pp. 602–605, Oct. 1996.Google Scholar
  17. 17.
    Sukkar, R.A., Lee, C.-H.: Vocabulary independent discriminative utterance verification for non-keyword rejection in subword based speech recognition. IEEE Trans. Speech and Audio Process. 4, 420–429 (1996)CrossRefGoogle Scholar
  18. 18.
    Sukkar, R. A., Setlur, A. R., Rahim, M. G., and Lee, C.-H., Utterance veri- fication of keyword string using word-based minimum verification error (WB- MVE) training, in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing (Atlanta), pp. 518–521, May 1996Google Scholar
  19. 19.
    Wald, A.: Sequential analysis. Chapman & Hall, NY (1947)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg  2012

Authors and Affiliations

  1. 1.Li Creative Technologies (LcT), IncFlorham ParkUSA

Personalised recommendations