Skip to main content

Speaker identification by using power distribution in frequency domain

  • Conference paper
  • 1420 Accesses

Abstract

The speech signal gives various levels of information. Firstly it conveys the words or message being spoken; also on a secondary level it gives us information about the identity of the speaker. The goal of speaker recognition is to extract the identity of the person speaking.

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

Buying options

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   159.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover 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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. S. Pruzansky, “Pattern-matching procedure for automatic talker recognition”, J.A.S.A., 35, pp. 354-358, 1963

    Google Scholar 

  2. G.R. Doddington, “A method of speaker verification”, J.A.S.A., 49,139 (A), 1971

    Google Scholar 

  3. P.D. Bricker, et. al., “Statistical techniques for talker identification”, B.S.T.J., 50, pp. 1427-1454, 1971

    Google Scholar 

  4. K.P. Li, et. al., “Experimental studies in speaker verification using a adaptive system”, J.A.S.A., 40, pp. 966-978, 1966

    Google Scholar 

  5. B. Beek, et al., “Automatic speaker recognition system”, Rome Air Development Center Report, 1971

    Google Scholar 

  6. M.R.Sambur, Speaker recognition and verification using linear prediction analysis, Ph. D. Dissert., M.I.T., 1972

    Google Scholar 

  7. S. Furui, et. al., “Talker recognition by long time averaged speech spectrum”, Electronics and Communications in Japan, 55-A. pp. 54-61, 1972

    Google Scholar 

  8. S. Furui, “Cepstral analysis technique for automatic speaker verification”, IEEE Trans. Acoustic, Speech, Signal Processing, ASSP-29, pp. 254-272, 1981

    Article  Google Scholar 

  9. A. E. Rosenberg and M. R. Sambur, “New Techniques for automatic speaker verification”, IEEE Trans. Acoustics, Speech, Signal Proc., ASSP-23, 2, pp. 169-176, 1975

    Article  Google Scholar 

  10. J. M. Naik, et. al., “Speaker verification over long distance telephone lines”, Proc. ICASSP, pp.524-527, 1989

    Google Scholar 

  11. F. K. Soong, et. al., “A vector quantization approach to speaker recognition”, At & T Technical Journal, 66, pp. 14-26, 1987

    Google Scholar 

  12. A. E. Rosenberg and F. K. Soong, “Evaluation of a vector quantization talker recognition system in text independent and text dependent models”, Computer Speech and Language 22, pp. 143-157, 1987

    Article  Google Scholar 

  13. R. Rose and R. A. Reynolds, “Text independent speaker identification using automatic acoustic segmentation”, Proc. ICASSP, pp. 293-296, 1990

    Google Scholar 

  14. T. Matsui and S. Furui, “Concatenated phoneme models for text variable speaker recognition”, Proc. ICASSP, pp. II-391-394, 1993

    Google Scholar 

  15. A. Higgins, et. al., “Speaker verification using randomized phrase prompting”, Digital Signal Processing, 1, pp. 89-106, 1991

    Article  Google Scholar 

  16. T. Matsui and S. Furui, “Similarity normalization method for speaker verification based on a posteriori probability”, Proc. ESCA Workshop on Automatic Speaker Recognition, Identification and Verification, pp. 59-62, 1994

    Google Scholar 

  17. D. Reynolds, “Speaker identification and verification using Gaussian mixture speaker models”, Proc. ESCA Workshop on Automatic Speaker recognition, Identification and verification, pp. 27-30, 1994

    Google Scholar 

  18. F. J. Bimbot, et. al., “A tutorial on textindependent speaker verification”, EURASIP Journ. on Applied Signal Processing, pp. 430- 451, 2004

    Google Scholar 

  19. G.R. Doddington, “Speaker recognition based on idiolectal differences between speakers”, Proc. Eurospeech, pp. 2521-2524, 2001

    Google Scholar 

  20. S Furui, “50 years of progress in speech and speaker recognition research”, ECTI Transactions on Computer and Information Technology, Vol. 1, No.2, November 2005.

    Google Scholar 

  21. Marco Grimaldi and Fred Cummins, “Speaker Identification using Instantaneous Frequencies”, IEEE Transactions on Audio, Speech, and Language Processing, vol., 16, no. 6, August 2008

    Google Scholar 

  22. H. B. Kekre, Tanuja K. Sarode, “Speech Data Compression using Vector Quantization”, WASET International Journal of Computer and Information Science and Engineering (IJCISE), Fall 2008, Volume 2, Number 4, pp.: 251-254, 2008. http://www.waset.org/ijcise.

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer India Pvt. Ltd

About this paper

Cite this paper

Kekre, H.B., Kulkarni, V. (2011). Speaker identification by using power distribution in frequency domain. In: Pise, S.J. (eds) Thinkquest~2010. Springer, New Delhi. https://doi.org/10.1007/978-81-8489-989-4_52

Download citation

  • DOI: https://doi.org/10.1007/978-81-8489-989-4_52

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-8489-988-7

  • Online ISBN: 978-81-8489-989-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics