Open Access

Power Spectral Density Error Analysis of Spectral Subtraction Type of Speech Enhancement Methods

EURASIP Journal on Advances in Signal Processing20062007:096384

https://doi.org/10.1155/2007/96384

Received: 8 August 2005

Accepted: 16 July 2006

Published: 18 September 2006

Abstract

A theoretical framework for analysis of speech enhancement algorithms is introduced for performance assessment of spectral subtraction type of methods. The quality of the enhanced speech is related to physical quantities of the speech and noise (such as stationarity time and spectral flatness), as well as to design variables of the noise suppressor. The derived theoretical results are compared with the outcome of subjective listening tests as well as successful design strategies, performed by independent research groups.

Keywords

Spectral DensityPower Spectral DensityPerformance AssessmentPower SpectralIndependent Research

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Authors’ Affiliations

(1)
Signal Processing Lab, School of Electrical Engineering, Royal Institute of Technology, Stockholm, Sweden

References

  1. Ohya T, Suda H, Miki T: 5.6 kbits/s PSI-CELP of the half-rate PDC speech coding standard. IEEE 44th Vehicular Technology Conference, June 1994, Stockholm, Sweden 3: 1680-1684.Google Scholar
  2. Ramabadran TV, Ashley JP, McLauglin MJ: Background noise suppression for speech enhancement and coding. Proceedings of the IEEE Workshop on Speech Coding for Telecommunications Proceeding, September 1997, Pocono Manor, Pa, USA 43-44.Google Scholar
  3. Yang J: Frequency domain noise suppression approaches in mobile telephone systems. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '93), April 1993, Minneapolis, Minn, USA 2: 363-366.Google Scholar
  4. Gibson JD, Koo B, Gray SD: Filtering of colored noise for speech enhancement and coding. IEEE Transactions on Signal Processing 1991,39(8):1732-1742. 10.1109/78.91144View ArticleGoogle Scholar
  5. Sörqvist P, Händel P, Ottersten B: Kalman filtering for low distortion speech enhancement in mobile communication. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97), April 1997, Munich, Germany 2: 1219-1222.Google Scholar
  6. Vary P: Noise suppression by spectral magnitude estimation—mechanism and theoretical limits. Signal Processing 1985,8(4):387-400. 10.1016/0165-1684(85)90002-7View ArticleGoogle Scholar
  7. Händel P: Low-distortion spectral subtraction for speech enhancement. Proceedings of the 4th European Conference on Speech Communication and Technology, September 1995, Madrid, Spain 2: 1549-1552.Google Scholar
  8. Boll SF: Suppression of acoustic noise in speech using spectral subtraction. IEEE Transactions on Acoustics, Speech, and Signal Processing 1979,27(2):113-120. 10.1109/TASSP.1979.1163209View ArticleGoogle Scholar
  9. Cappe O: Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor. IEEE Transactions on Speech and Audio Processing 1994,2(2):345-349. 10.1109/89.279283View ArticleGoogle Scholar
  10. Cappe O, Laroche J: Evaluation of short-time spectral attenuation techniques for the restoration of musical recordings. IEEE Transactions on Speech and Audio Processing 1995,3(1):84-93. 10.1109/89.365378View ArticleGoogle Scholar
  11. Hansen JHL, Clements MA: Constrained iterative speech enhancement with application to speech recognition. IEEE Transactions on Signal Processing 1991,39(4):795-805. 10.1109/78.80901View ArticleGoogle Scholar
  12. Lockwood P, Boudy J, Blanchet M: Non-linear spectral subtraction (NSS) and hidden Markov models for robust speech recognition in car noise environments. Proceedings of IEEE International Conference Acoustics, Speech, and Signal Processing (ICASSP '92), March 1992, San Francisco, Calif, USA I: 265-268.Google Scholar
  13. Wang DL, Lim JS: The unimportance of phase in speech enhancement. IEEE Transactions on Acoustics, Speech, and Signal Processing 1982,30(4):679-681. 10.1109/TASSP.1982.1163920View ArticleGoogle Scholar
  14. Wiener N: Extrapolation, Interpolation, and Smoothing of Stationary Time Series: With Engineering Applications, Principles of Electrical Engineering Series. MIT Press, Cambridge, Mass, USA; 1949.MATHGoogle Scholar
  15. Lim JS, Oppenheim AV: Enhancement and bandwidth compression of noisy speech. Proceedings of the IEEE 1979,67(12):1586-1604.View ArticleGoogle Scholar
  16. Sim BL, Tong YC, Chang JS, Tan CT: A parametric formulation of the generalized spectral subtraction method. IEEE Transactions on Speech and Audio Processing 1998,6(4):328-336. 10.1109/89.701361View ArticleGoogle Scholar
  17. Sovka P, Pollak P, Kybic J: Extended spectral subtraction. Proceedings of the 5th European Conference on Speech Communication and Technology, September 1995, Trieste, Italy 963-966.Google Scholar
  18. Stoica P, Nehorai A: On the asymptotic distribution of exponentially weighted prediction error estimators. IEEE Transactions on Acoustics, Speech, and Signal Processing 1988,36(1):136-139. 10.1109/29.1504MathSciNetView ArticleGoogle Scholar
  19. Stoica P, Moses R: Introduction to Spectral Analysis. Prentice Hall, Upper Saddle River, NJ, USA; 1997.MATHGoogle Scholar
  20. Peeters TTJM, Ciftcioglu Ö: Statistics on exponential averaging of periodograms. IEEE Transactions on Signal Processing 1995,43(7):1631-1636. 10.1109/78.398724View ArticleGoogle Scholar
  21. Angeby J, Stoica P, Söderström T: Asymptotic statistical analysis of autoregressive frequency estimates. Signal Processing 1994,39(3):277-292. 10.1016/0165-1684(94)90090-6View ArticleMATHGoogle Scholar
  22. Händel P, Stoica P, Söderström T: Asymptotic variance of the AR spectral estimator for noisy sinusoidal data. Signal Processing 1994,35(2):131-139. 10.1016/0165-1684(94)90041-8View ArticleMATHGoogle Scholar
  23. Kushner WM, Goncharoff V, Wu C, Nguyen V, Damoulakis JN: The effects of subtractive-type speech enhancement/noise reduction algorithms on parameter estimation for improved recognition and coding in high noise environments. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '89), May 1989, Glasgow, Scotland 1: 211-214.Google Scholar

Copyright

© Peter Händel. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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