A Method of Automatic Speaker Recognition Using Cepstral Features and Vectorial Quantization

  • José Ramón Calvo de Lara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3773)


Automatic Speaker Recognition techniques are increasing the use of the speaker’s voice to control access to personalized telephonic services. This paper describes the use of vector quantization as a feature matching method, in an automatic speaker recognition system, evaluated with speech samples from a SALA Spanish Venezuelan database for fixed telephone network. Results obtained reflect a good performance of the method in a text independent job in the context of sequences of digits.


Speaker Recognition Speaker Verification Speaker Identification Acoustic Vector Cepstral Feature 
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.
    Do, M.N.: An Automatic Speaker Recognition System. In: Audio Visual Communications Laboratory, Swiss Federal Institute of Technology, Lausanne, Switzerland (2001),
  2. 2.
    Reynolds, D.A.: An Overview of Automatic Speaker Recognition Technology, MIT Lincoln Laboratory, Lexington, MA, USA, This paper appears in ICASSP 2002, pp. 4072–4075 (2002)Google Scholar
  3. 3.
    Kinnunen, T.: Spectral Features for Automatic Text-Independent Speaker Recognition, University of Joensuu, Department of Computer Science, Joensuu, Finland, December 21 (2003),
  4. 4.
    Campbell Jr., J.P.: Speaker Recognition: A tutorial. DoD. Proceedings of the IEEE 85(9), 1437–1462 (1997)CrossRefGoogle Scholar
  5. 5.
    Mason, J., Zhang, X.: Velocity and acceleration features in speaker recognition, Department of Electrical & Electronic Engineering, Univ. Coll., Swansea. This paper appears in ICASSP 1991, pp. 3673–3676 (1991)Google Scholar
  6. 6.
    Song, F.K., Rosenberg, A.E., Juang, B.H.: A vector quantisation approach to speaker recognition. AT&T Technical Journal 66(2), 14–26 (1987)Google Scholar
  7. 7.
    Linde, Y., Buzo, A., Gray, R.: An algorithm for vector quantizer design. IEEE Transactions on Communications 28, 84–95 (1980)CrossRefGoogle Scholar
  8. 8.
    Maldonado, L., Mora, E.: Universidad de los Andes, Mérida, Venezuela: Personal communications with the author (2004)Google Scholar
  9. 9.
    Moreno, A., Comeyne, R., Haslam, K., van den Heuvel, H., Höge, H., Horbach, S., Micca, G.: SALA: SpeechDat Across Latin America: Results Of The First Phase. In: LREC 2000: 2nd International Conference on Language Resources & Evaluation, Athens, Greece (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • José Ramón Calvo de Lara
    • 1
  1. 1.Advanced Technologies Application Center, CENATAVCuba

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