A parametric formulation of the generalized spectral subtraction method

In this paper, two short-time spectral amplitude estimators of the speech signal are derived based on a parametric formulation of the original generalized spectral subtraction method. The objective is to improve the noise suppression performance of the original method while maintaining its computational simplicity. The proposed parametric formulation describes the original method and several of its modifications. Based on the formulation, the speech spectral amplitude estimator is derived and optimized by minimizing the mean-square error (MSE) of the speech spectrum. With a constraint imposed on the parameters inherent in the formulation, a second estimator is also derived and optimized. The two estimators are different from those derived in most modified spectral subtraction methods, which are predominantly nonstatistical. When tested under stationary white Gaussian noise and semistationary Jeep noise, they showed improved noise suppression results.

[1]  Olivier Cappé,et al.  Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor , 1994, IEEE Trans. Speech Audio Process..

[2]  Barry M. G. Cheetham,et al.  Speech enhancement employing spectral subtraction and linear predictive analysis , 1993 .

[3]  B. Picinbono Random Signals and Systems , 1993 .

[4]  S. V. Vaseghi,et al.  Restoration of Old Gramophone Recordings , 1992 .

[5]  R. McAulay,et al.  Speech enhancement using a soft-decision noise suppression filter , 1980 .

[6]  David Malah,et al.  Speech enhancement using a minimum mean-square error log-spectral amplitude estimator , 1984, IEEE Trans. Acoust. Speech Signal Process..

[7]  J. S. Chang,et al.  A micropower-compatible time-multiplexed SC speech spectrum analyzer design , 1993 .

[8]  George S. Kang,et al.  Quality improvement of LPC-processed noisy speech by using spectral subtraction , 1989, IEEE Trans. Acoust. Speech Signal Process..

[9]  Y. C. Tong,et al.  A low power time-multiplexed SC speech spectrum analyzer , 1989, Symposium 1989 on VLSI Circuits.

[10]  Thomas W. Parsons,et al.  Study and Development of the INTEL Technique for Improving Speech Intelligibility , 1975 .

[11]  S. Boll,et al.  Suppression of acoustic noise in speech using spectral subtraction , 1979 .

[12]  A.V. Oppenheim,et al.  Enhancement and bandwidth compression of noisy speech , 1979, Proceedings of the IEEE.

[13]  Richard M. Schwartz,et al.  Enhancement of speech corrupted by acoustic noise , 1979, ICASSP.

[14]  Ronald E. Crochiere,et al.  A weighted overlap-add method of short-time Fourier analysis/Synthesis , 1980 .

[15]  Jae S. Lim,et al.  The unimportance of phase in speech enhancement , 1982 .

[16]  Vladimir Goncharoff,et al.  The effects of subtractive-type speech enhancement/noise reduction algorithms on parameter estimation for improved recognition and coding in high noise environments , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[17]  G M Clark,et al.  Two-component hearing sensations produced by two-electrode stimulation in the cochlea of a deaf patient. , 1983, Science.

[18]  John H. L. Hansen,et al.  Discrete-Time Processing of Speech Signals , 1993 .

[19]  Jae Lim,et al.  Evaluation of a correlation subtraction method for enhancing speech degraded by additive white noise , 1978 .

[20]  Ephraim Speech enhancement using a minimum mean square error short-time spectral amplitude estimator , 1984 .