Skip to main content

Speaker Verification Based on Wavelet Packets

  • Conference paper
Book cover Text, Speech and Dialogue (TSD 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3206))

Included in the following conference series:

Abstract

Alternative ways to represent speaker’s voice individuality are studied for the task of speaker verification. We exploit a set of orthonormal bases provided by wavelet packets that allow an effective manipulation of the frequency subbands according to the critical bands concept. Novel wavelet packet based sets of speech features are contrasted with existing wavelet features as well as with the widely accepted Mel-scale cepstral coefficients (MFCC). Our scheme differs from previous wavelet-based works, primarily in the wavelet-packet tree design that follows the concept of critical bandwidth, as well as in the particular wavelet basis function that have been used. Comparative experimental results confirm the assertion that the proposed speech features outperform MFCC, as well as previously used wavelet features, on the task of speaker verification.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Moore, B.C.J.: An introduction to the psychology of hearing. Academic Press, London (2003)

    Google Scholar 

  2. Tufekci, Z., Gowdy, J.N.: Feature extraction using discrete wavelet transform for speech recognition. In: Proc. of IEEE Southeastcon 2000, pp. 116–123 (2000)

    Google Scholar 

  3. Long, C.J., Datta, S.: Wavelet based feature extraction for phoneme recognition. In: Proc. of 4th Int. Conf. of Spoken Language Processing, Philadelphia, USA, vol. 1, pp. 264–267 (1996)

    Google Scholar 

  4. Davis, S.B., Mermelstein, P.: Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences. IEEE Trans. Acoustic, Speech and Signal Processing ASSP-28(4), 357–366 (1980)

    Article  Google Scholar 

  5. Sarikaya, R., Hansen, H.L.: High resolution speech feature parameterization for monophone-based stressed speech recognition. IEEE Signal Processing Letters 7(7), 182–185 (2000)

    Article  Google Scholar 

  6. Farooq, O., Datta, S.: Mel-scaled wavelet filter based features for noisy unvoiced phoneme recognition. In: Proc. of ICSLP 2002, Denver, Colorado, USA, September 16-20, pp. 1017–1020 (2002)

    Google Scholar 

  7. Sarikaya, R., Pellom, B.L., Hansen, H.L.: Wavelet packet transform features with application to speaker identification. In: Proc. of IEEE Nordic Signal Processing Symposium, Visgo, Denmark, pp. 81–84 (1998)

    Google Scholar 

  8. Mallat, S.: A wavelet tour of signal processing. Academic Press, San Diego (1998)

    MATH  Google Scholar 

  9. Erzin, E., Cetin, A.E., Yardimci, Y.: Subband analysis for speech recognition in the presence of car noise. In: Proc. of ICASSP 1995, Detroit, MI, vol. 1, pp. 417–420 (1995)

    Google Scholar 

  10. Rabiner, L.R., Cheng, M.J., Rosenberg, A.E., McGonegal, C.A.: A Comparative Performance Study of Several Pitch Detection Algorithms. IEEE Transactions on ASSP ASSP-24(5), 399–418 (1976)

    Article  Google Scholar 

  11. The NIST Year 2001 Speaker Recognition Evaluation Plan. NIST of USA (2001), Available: http://www.nist.gov/speech/tests/spk/2001/doc/2001-spkrec-evalplan-v05.9.pdf

  12. Ganchev, T., Fakotakis, N., Kokkinakis, G.: Text-Independent Speaker Verification Based on Probabilistic Neural Networks. In: Proc. of Acoustics 2002, Patras, Greece, pp. 159–166 (2002)

    Google Scholar 

  13. The NIST Year 2002 Speaker Recognition Evaluation Plan. NIST of USA (2002), Available: http://www.nist.gov/speech/tests/spk/2002/doc/2002-spkrec-evalplan-v60.pdf

  14. Fletcher, H.: Auditory patterns. Reviews of Modern Physics (12), 47–65 (1940)

    Google Scholar 

  15. Zwicker, E.: Subdivision of the audible frequency range into critical bands (Frequenzgruppen). The J. of Acoustical Society of America 33, 248–249 (1961)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ganchev, T., Siafarikas, M., Fakotakis, N. (2004). Speaker Verification Based on Wavelet Packets. In: Sojka, P., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2004. Lecture Notes in Computer Science(), vol 3206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30120-2_38

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-30120-2_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23049-6

  • Online ISBN: 978-3-540-30120-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics