An Improved Speech Enhancement Algorithm Based on Wiener-Filtering

Abstract:

This paper proposes an improved speech enhancement algorithm based on Wiener-Filtering, which addresses the problems of speech distortion and musical noise. The proposed algorithm adopts the masking properties of human auditory system on calculating the gain of spectrum point, in order that the signal in the enhanced speech whose energy is lower than the threshold will not be decreased further and the less distortion will be brought to enhanced speech by the trade-off between the noise elimination and speech signal distortion. What’s more, in order to eliminate the “musical noise”, a spectrum-shaping technology using averaging method between adjacent frames is adopted. And to guarantee the real-time application, two-stage moving-average strategy is adopted. The computer simulation results show that the proposed algorithm is superior to the traditional Wiener method in the low CPU cost, real-time statistics, the reduction of the speech distortion and residual musical noise.

• Periodical: Advanced Materials Research (Volumes 989-994)
• Pages: 2565-2568
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.989-994.2565
• Online since: July 2014
• Authors: Yu Hong Liu*, Dong Mei Zhou, Jing Di
• Keywords: Masking Properties of Human Auditory System, Spectrum-Shaping, Speech Enhancement, Wiener-Filtering

References

[1] Y. Ephraim and D. Malah, Speech enhancement using a minimum mean square error short-time spectral amplitude estimator, IEEE Trans Acoust, Speech, Signal Processing, vol. ASSP-32, pp.1109-1121, Dec (1984).

DOI: 10.1109/tassp.1984.1164453

[2] R. Schwartz M. Berouti and J. Makhoul, Enhancement of speech corrupted by acoustic noise, Proc. of ICASSP, 1979, vol. I, pp.208-211.

DOI: 10.1109/icassp.1979.1170788

[3] 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, (1999).

DOI: 10.1109/89.748118

[4] Y. Ephraim and H.L. Van Trees, A signal subspace approach for speech enhancement, IEEE Trans. Speech and Audio Processing, vol. 3, pp.251-266, (1995).

DOI: 10.1109/89.397090

[5] QiLi, Jiangsong Zheng, Augustine Tsai, et al, Robust Endpoint Detect and Energy Normalization for Real-Time Speech and Speaker Recognition, IEEE Transactions on Acoustic, Speech and Audio Processing, pp.146-157, (2002).

DOI: 10.1109/tsa.2002.1001979

[6] Y. Hu and P. Loizou, lncorporating a psychoacoustic model in frequency domain speech enhancement, IEEE Signal Processing Letters, vol. 11(2), pp.270-273, (2004).

DOI: 10.1109/lsp.2003.821714

[7] Y. Hu and P. c. Loizou, A perceptually motivated approach for speech enhancement, IEEE Trans. Speech Audio Processing, pp.457-465. Sept. (2003).

DOI: 10.1109/tsa.2003.815936