Skip to main content
SpringerLink
Log in

Speech Hashing Algorithm Based on Short-Time Stability

  • Conference paper
Artificial Neural Networks – ICANN 2009 (ICANN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5769))

Included in the following conference series:

Abstract

The performance of a perceptual hashing system, which is often measured by discrimination and robustness, is directly related to the features that the system extracts. In this letter, a new speech hashing scheme based on short-time stability is presented. The characteristic of natural speech that the principal components of linear prediction coefficients among neighboring frames tend to be very similar is utilized to generate the hash sequence. Experimental results demonstrate the effectiveness of the proposed scheme in terms of discrimination and robustness.

This work was supported in part by the National Natural Science Foundation of China (No. 60872115), in part by the Shanghai’s Key Discipline Development Program (No.J50104), and in part by the International Cooperation Foundation Program of Shanghai (No. 075107035).

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
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. Haitsma, J., Kalker, T.: A highly robust audio fingerprinting system. In: Proc. ISMIR, vol.  2002 (2002)

    Google Scholar 

  2. Menezes, A.J., Van Oorschot, P.C., Vanstone, S.A.: Handbook of applied cryptography. CRC Press, Boca Raton (1997)

    MATH  Google Scholar 

  3. Seo, J.S., Haitsma, J., Kalker, T., Yoo, C.D.: A robust image fingerprinting system using the Radon transform. Signal Processing: Image Communication 19(4), 325–339 (2004)

    Google Scholar 

  4. Cano, P., Batlle, E., Kalker, T., Haitsma, J.: A review of audio fingerprinting. The Journal of VLSI Signal Processing 41(3), 271–284 (2005)

    Article  Google Scholar 

  5. Fragoulis, D., Rousopoulos, G., Panagopoulos, T., Alexiou, C., Papaodysseus, C.: On the automated recognition of seriously distorted musical recordings. IEEE Transactions on Signal Processing 49(4), 898–908 (2001)

    Article  Google Scholar 

  6. Ramalingam, A., Krishnan, S.: Gaussian mixture modeling of short-time Fourier transform features for audio fingerprinting. IEEE Transactions on Information Forensics and Security 1(4), 457–463 (2006)

    Article  Google Scholar 

  7. Sethi, I., Kulesh, V., Petrushin, V.: Indexing and retrieval of music via gaussian mixture models. In: Proc. 3rd Int. Workshop on Content Based Multimedia Indexing, vol. 2003 (2003)

    Google Scholar 

  8. Allamanche, E., Herre, J., Hellmuth, O., Froba, B., Cremer, M.: AudioID: Towards content-based identification of audio material. Preprints-Audio Engineering Society (2001)

    Google Scholar 

  9. Park, M., Kim, H., Yang, S.H.: Frequency-temporal filtering for a robust audio fingerprinting scheme in real-noise environments. ETRI journal 28(4), 509–512 (2006)

    Article  Google Scholar 

  10. Özer, H., Sankur, B., Memon, N., Anarim, E.: Perceptual audio hashing functions. EURASIP Journal on Applied Signal Processing 2005(1), 1780–1793 (2005)

    Article  Google Scholar 

  11. Seo, J.S., Jin, M., Lee, S., Jang, D., Lee, S.: Audio fingerprinting based on normalized spectral subband centroids. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005. Proceedings(ICASSP 2005), vol. 3 (2005)

    Google Scholar 

  12. Seo, J.S., Jin, M., Lee, S., Jang, D., Lee, S., Yoo, C.D.: Audio fingerprinting based on normalized spectral subband moments. IEEE Signal Processing Letters 13(4), 209–212 (2006)

    Article  Google Scholar 

  13. Jiao, Y., Yang, B., Li, M., Niu, X.: MDCT-Based Perceptual Hashing for Compressed Audio Content Identification. In: IEEE 9th Workshop on Multimedia Signal Processing, 2007. MMSP 2007, pp. 381–384 (2007)

    Google Scholar 

  14. Jiao, Y., Li, M., Li, Q., Niu, X.: Key-Dependent Compressed Domain Audio Hashing. In: Eighth International Conference on Intelligent Systems Design and Applications, ISDA 2008, vol. 3 (2008)

    Google Scholar 

  15. Niu, X.M., Jiao, Y.H.: An overview of perceptual hashing. Acta Electronica Sinica 36(7), 1405–1411 (2008)

    Google Scholar 

  16. Jiao, Y., Li, Q., Niu, X.: Compressed Domain Perceptual Hashing for MELP Coded Speech. In: International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2008, pp. 410–413 (2008)

    Google Scholar 

  17. Nichols, R.K., Lekkas, P.C.: Wireless security: models, threats, and solutions. McGraw-Hill, New York (2002)

    Google Scholar 

  18. Green, D.R.: The utility of higher-order statistics in gaussian noise suppression. US Government Authored or Collected Report, Naval Postgraduate School, Memory, Calif, USA (2003)

    Google Scholar 

  19. Jackson, L.B.: Digital filters and signal processing. Kluwer Academic Publishers, Dordrecht (1985)

    Google Scholar 

  20. Gersho, A., Gray, R.M.: Vector quantization and signal compression. Springer, Heidelberg (1992)

    Book  MATH  Google Scholar 

  21. Swaminathan, A., Mao, Y., Wu, M.: Robust and secure image hashing. IEEE Transactions on Information Forensics and Security 1(2), 215–230 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Communication and Information Engineering, Shanghai University, Shanghai, 200072, China

    Ning Chen & Wang-Gen Wan

Authors
  1. Ning Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wang-Gen Wan
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Dipartimento di Elettronica, Politecnico di Milano, Piazza L. da Vinci 32, 20133, Milano, Italy

    Cesare Alippi

  2. Department of Electrical and Computer Engineering, University of Cyprus, 75 Kallipoleos Street, 1678, Nicosia, Cyprus

    Marios Polycarpou , Christos Panayiotou  & Georgios Ellinas ,  & 

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chen, N., Wan, WG. (2009). Speech Hashing Algorithm Based on Short-Time Stability. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds) Artificial Neural Networks – ICANN 2009. ICANN 2009. Lecture Notes in Computer Science, vol 5769. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04277-5_43

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04277-5_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04276-8

  • Online ISBN: 978-3-642-04277-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation