Skip to main content
SpringerLink
Log in

Single-Microphone Noise Suppression for 3G Handsets Based on Weighted Noise Estimation

  • Chapter
Speech Enhancement

Part of the book series: Signals and Communication Technology ((SCT))

Abstract

A noise suppression algorithm with high speech quality based on weighted noise estimation is presented. This algorithm continuously updates the estimated noise by weighted noisy speech in accordance with an estimated SNR. With a better noise estimate, a more correct SNR is obtained, resulting in the enhanced speech with low distortion. Subjective evaluation results show that five-grade mean opinion scores of this algorithm with a speech codec is improved by as much as 0.35, compared with either the MMSE-STSA or the EVRC noise suppression algorithm. A noise suppressor based on a later version of this noise suppression algorithm satisfies all the 3GPP minimum performance requirements. It is employed in the world’s first 3G handset equipped with a 3GPP-endorsed noise suppressor.

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

Access this chapter

Log in via an institution
eBook
USD 16.99
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
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. S. F. Boll, “Suppression of acoustic noise in speech using spectral subtraction,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-27, pp. 113–120, Apr. 1979.

    Article  Google Scholar 

  2. J. S. Lim and A. V. Oppenheim, “Enhancement and bandwidth compression of noisy speech,” Proc. of the IEEE, vol. 67, pp. 1586–1604, Dec. 1979.

    Google Scholar 

  3. R. J. McAulay and M. L. Malpass, “Speech enhancement using a soft-decision noise suppression filter,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-28, pp. 137–145, Apr. 1980.

    Article  Google Scholar 

  4. Y. Ephraim and D. Malah, “Speech enhancement using a minimum meansquare error short-time spectral amplitude estimator,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-32, pp. 1109–1121, Dec. 1984.

    Article  Google Scholar 

  5. Y. Ephraim and D. Malah, “Speech enhancement using a minimum meansquare error log-spectral amplitude estimator,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-33, pp. 443–445, Apr. 1985.

    Article  Google Scholar 

  6. N. Virag, “Single channel speech enhancement based on masking properties of the human auditory system,” IEEE Trans. Speech and Audio Processing, vol. 7, pp. 126–137, Mar. 1999.

    Article  Google Scholar 

  7. Z. Goh, K.-C. Tan, and B. T. G. Tan, “Kalman-filtering speech enhancement method based on a voiced-unvoiced speech model,” IEEE Trans. Speech and Audio Processing, vol. 7, pp. 510–524, Sept. 1999.

    Article  Google Scholar 

  8. B. Widrow, J. R. Grover, Jr., J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. r. Zeidler, E. Dong, Jr., and R. C. Goodlin, “Adaptive noise cancelling: principles and applications,” Proc. of the IEEE, vol. 63, pp. 1692–1716, Dec. 1975.

    Google Scholar 

  9. S. F. Boll and D. C. Publisher, “Suppression of acoustic noise in speech using two microphone adaptive noise cancellation,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-28, pp. 752–753, Dec. 1980.

    Article  Google Scholar 

  10. M. J. Al-Kindi and J. Dunlop, “A low distortion adaptive noise cancellation structure for real time applications,” in Proc. IEEE ICASSP, 1987, pp. 2153–2156.

    Google Scholar 

  11. J. Dunlop and M. J. Al-Kindi, “Application of adaptive noise cancelling to diver voice communication,” in Proc. IEEE ICASSP, 1987, pp. 1708–1711.

    Google Scholar 

  12. G. Mirchandani, R. L. Zinser, and J. B. Evans, “A New Adaptive Noise Cancellation Scheme in the Presence of Crosstalk,” IEEE Trans. Circuits and Systems, vol. 39, pp. 681–694, Oct. 1992.

    Article  MATH  Google Scholar 

  13. V. Parsa, P. A. Parker, and R. N. Scott, “Performance analysis of a crosstalk resistant adaptive noise canceller,” IEEE Trans. Circuits and Systems, vol. 43, pp. 473–482, July 1996.

    Article  Google Scholar 

  14. S. Ikeda and A. Sugiyama, “An adaptive noise canceller with low signal distortion for speech codecs,” IEEE Trans. Signal Processing, vol. 47, pp.665–674, Mar. 1999.

    Article  Google Scholar 

  15. S. Ikeda and A. Sugiyama, “An adaptive noise canceller with low signaldistortion in the presense of crosstalk,” IEICE Trans. Fund., vol. E82-A, pp. 1517–1525, Aug. 1999.

    Google Scholar 

  16. T. V. Ramabadran, J. P. Ashley, and M. J. McLaughlin, “Background noise suppression for speech enhancement and coding,” in IEEE Workshop on Speech Coding and Tel., 1997, pp. 43–44.

    Google Scholar 

  17. D. Malah, R. V. Cox, and A. J. Accardi, “Tracking speech-presence uncertainty to improve speech enhancement in non-stationary noise environments,” in Proc. IEEE ICASSP, 1999, pp. 789–792.

    Google Scholar 

  18. N. S. Kim and J. H. Chang, “Spectral enhancement based on global soft decision,” IEEE Signal Processing Letters, vol. 7, pp. 108–110, May 2000.

    Article  Google Scholar 

  19. M. Berouti, R. Schwartz, and J. Makhoul, “Enhancement of speech corrupted by acoustic noise,” in Proc. IEEE ICASSP, 1979, pp. 208–211.

    Google Scholar 

  20. 3GPP TS 26.077, Minimum Performance Requirements for Noise Suppresser Application to the AMR Speech Encoder. Mar. 2001.

    Google Scholar 

  21. O. Cappe, “Elimination of the musical noise phenomenon with Ephraim and Malah noise suppressor,” IEEE Trans. Speech Audio Processing, vol. 2, pp. 345–349, Apr. 1994.

    Article  Google Scholar 

  22. P. Scalart and J. V. Filho, “Speech enhancement based on a priori signal to noise estimation,” in Proc. IEEE ICASSP, 1996, pp. 629–632.

    Google Scholar 

  23. TIA/EIA/IS-127, Enhanced Variable Rate Codec. 1996.

    Google Scholar 

  24. M. Abramowitz and I. A. Stegun, Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. John Wiley & Sons, 1964.

    Google Scholar 

  25. R. Martin, “Spectral subtraction based on minimum statistics,” in Proc. EUSIPCO, 1994, pp. 1182–1185.

    Google Scholar 

  26. R. Martin, “An MMSE soft-decision estimation for combined noise and residual echo reduction,” in Proc. IWAENC, 1999, pp. 84–87.

    Google Scholar 

  27. V. Stahl, A. Fischer, and R. Bippus, “Quantile based noise estimation for spectral subtraction and Wiener filtering,” in Proc. IEEE ICASSP, 2000, pp. 1875–1878.

    Google Scholar 

  28. S. Gustafsson, P. Jax, and P. Vary, “A novel psychoacoustically motivated audio enhancement algorithm preserving background noise characteristics,” in Proc. IEEE ICASSP, 1998, pp. 397–400.

    Google Scholar 

  29. T. Gulzow, “Spectral-subtraction-based speech enhancement using a new estimation technique for non-stationary noise,” in Proc. IWAENC, 1999, pp. 76–79.

    Google Scholar 

  30. J. D. Johnston, “Transform coding of audio signal using perceptual noise criteria,” IEEE J. of Selec. Areas Commun., vol. 6, pp. 314–323, Feb. 1988.

    Article  Google Scholar 

  31. B. Sawa, M. Nashioka, K. Nakamura, and M. Enoki, “Cellular telephones and PHS terminals,” Toshiba Review, vol. 54, pp. 38–43, Apr. 1999 (in Japanese).

    Google Scholar 

  32. 3GPP TS 26.978, Results of the AMR Noise Suppression Selection Phase. Mar. 2001.

    Google Scholar 

  33. 3GPP TS 26.975, Performance Characterization of the AMR Speech Codec. Apr. 2001.

    Google Scholar 

  34. ITU-T COM 12, Methods for Subjective Determination of Transmission Quality. Recommendation P.800.

    Google Scholar 

  35. A. Sugiyama, T. P. Hua, M. Kato, and M. Serizawa, “Noise suppression with synthesis windowing and pseudo noise injection,” in Proc. IEEE ICASSP, 2002, pp. 545–548.

    Google Scholar 

  36. M. Kato, A. Sugiyama, and M. Serizawa, “A family of 3GPP noise suppressors for the AMR codec and the evaluation results,” in Proc. IEEE ICASSP, 2003, pp. 916–919.

    Google Scholar 

  37. “TSG SA WG4 status report at TSG SA#17,” TSGS#16-020431, Sept. 2002.

    Google Scholar 

  38. M. Kato, M. Serizawa, N. Toki, U. Mori, Y. Morishita, and K. Hayashi, “Noise suppression with high speech quality based on weighted noise estimation for 3G handsets,” NEC Res. & Develop., vol. 44, pp. 65–73, Oct. 2003.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Media and Information Research Laboratories, NEC Corporation Kawasaki, Kanagawa, 211-8666, Japan

    Akihiko Sugiyama, Masanori Kato & Masahiro Serizawa

Authors
  1. Akihiko Sugiyama
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Masanori Kato
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Masahiro Serizawa
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Sugiyama, A., Kato, M., Serizawa, M. (2005). Single-Microphone Noise Suppression for 3G Handsets Based on Weighted Noise Estimation. In: Speech Enhancement. Signals and Communication Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-27489-8_6

Download citation

  • DOI: https://doi.org/10.1007/3-540-27489-8_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24039-6

  • Online ISBN: 978-3-540-27489-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation