Advertisement

Study on Text-Dependent Speaker Recognition Based on Biomimetic Pattern Recognition

  • Shoujue Wang
  • Yi Huang
  • Yu Cao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)

Abstract

We studied the application of Biomimetic Pattern Recognition to speaker recognition. A speaker recognition neural network using network matching degree as criterion is proposed. It has been used in the system of text-dependent speaker recognition. Experimental results show that good effect could be obtained even with lesser samples. Furthermore, the misrecognition caused by untrained speakers occurring in testing could be controlled effectively. In addition, the basic idea “cognition” of Biomimetic Pattern Recognition results in no requirement of retraining the old system for enrolling new speakers.

Keywords

Radial Basis Function Feature Space Speech Signal Radial Basis Function Neural Network Speaker Recognition 
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.

Unable to display preview. Download preview PDF.

References

  1. Campbell, J.P.: Speaker Recognition: A Tutorial. Proceedings of the IEEE 85(9), 1437–1462 (1997)CrossRefGoogle Scholar
  2. Farrel, K.R., Mammone, R.J., Assaleh, K.T.: Speaker Recognition Using Neural Networks and Conventional Classifiers. IEEE Transactions on Speech and Audio Processing 2(1), 194–205 (1994)CrossRefGoogle Scholar
  3. Oglesby, J., Mason, J.S.: Radial Basis Function Networks for Speaker Recognition. In: Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 1, pp. 393–396 (1991)Google Scholar
  4. Finan, R.A., Sapeluk, A.T., Damper, R.I.: Comparison of Multilayer and Radial Basis Function Neural Networks for Text-Dependent Speaker Recognition. In: IEEE International Conference on Neural Networks - Conference Proceedings, vol. 4, pp. 1992–1997 (1996)Google Scholar
  5. Wang, S.: Bionic (topological) Pattern Recognition - A New Model of Pattern Recog-nition Theory and Its Applications (in Chinese). Acta Electronica Sinica 30(10), 1417–1420 (2002)Google Scholar
  6. Qin, H., Wang, S.: Comparison of Biomimetic Pattern Recognition, HMM and DTW for Speaker-Independent Speech Recognition (in Chinese). Acta Electronica Sinica 33(5), 957–960 (2005)Google Scholar
  7. Vapnik, V.N.: The Nature of Statistic Learning Theory. Springer, Heidelberg (1995)Google Scholar
  8. Wang, S., Wang, B.: Analysis and Theory of High-Dimension Space Geometry for Artificial Neural Networks (in Chinese). Acta Electronica Sinica 30(1), 1–4 (2002)MATHGoogle Scholar
  9. Wang, S., Li, Z., Chen, X., Wang, B.: Discussion on the Basic Mathematical Models of Neurons in General Purpose Neurocomputer (in Chinese). Acta Electronica Sinica 29(5), 577–580 (2001)MathSciNetGoogle Scholar
  10. Wang, S., Zhao, X.: Biomimetic Pattern Recognition Theory and Its Applications. Chinese Journal of Electronics 13(3), 373–377 (2004)Google Scholar
  11. Quatieri, T.F.: Discrete-Time Speech Signal Processing: Principles and Practice. Prentice Hall, Englewood Cliffs (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shoujue Wang
    • 1
  • Yi Huang
    • 1
  • Yu Cao
    • 1
  1. 1.Lab of Artificial Neural Networks, Institute of SemiconductorsChinese Academy of SciencesBeijingChina

Personalised recommendations