An Non-Contact Speech Enhancement Algorithm Based on Lifting Scheme

Abstract:

The traditional method for detecting speech signal needs the help of microphone, which must be placed closely to the body of human beings. To some extent, this method would bring several inconveniences. Non-contact speech detection method breaks through the limitation of the traditional method, this new kind of speech obtaining method can detect speech signal quite well even in strong noisy background. However, this non-contact speech detecting system also produces some electromagnetic noise and circuit noise, which reduced the quality of radar speech signal. Therefore, based on the good time-frequency analyze performance, the lifting scheme was also proposed in this paper to remove noise from radar speech. Comparing to classical enhancement algorithm, such as spectral subtraction and Wiener filter, the proposed algorithm can remove the component of noise availably and reserve the original pure speech signal in a promising way.

• Periodical: Applied Mechanics and Materials (Volumes 513-517)
• Pages: 3813-3817
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.513-517.3813
• Online since: February 2014
• Authors: Hui Jun Xue, Sheng Li, Teng Jiao, Yang Zhang, Hao Lv, Xiao Yu, Guo Hua Lu, Hua Zhang, Jian Qi Wang*
• Keywords: Lifting Scheme, Non-Contact Speech, Non-Contact Speech Enhancement, Spectrogram

References

[1] Sheng Li, J. Q. Wang, T. Liu, X. J. Jing. Wavelet packet entropy for millimeter wave conducted speech enhancement[J]. Noise Control Engineering Journal, 2009 57 543-550.

DOI: 10.3397/1.3194789

[2] S. Li, J. Q. Wang, M. Niu, T. Liu, X. J. Jing. Millimeter wave conduct speech enhancement based on auditory masking properties[J]. Microwave and Optical Technology Letters, 2008 50 2109–2114.

DOI: 10.1002/mop.23588

[3] Z. W. Li. Millimeter wave radar for detecting the speech signal applications[J]. Int. J. Infrared Mill Wave, 1996 17 2175-2183.

DOI: 10.1007/bf02069493

[4] J. F. Holzrichter, G. C. Burnett, L. C. Ng, W. A. Lea. Speech articulator measurements using lowpower EM-wave sensors[J]. Acoust. Soc. Am, 1998 103 622-625.

DOI: 10.1121/1.421133

[5] S. F. Boll. Suppression of acoustic noise in speech using spectral subtraction[J]. IEEE Trans. Acoust. Speech Signal Process, 1979 27 113-120.

DOI: 10.1109/tassp.1979.1163209

[6] H. Sameti, H. Sheikhzadeh, L. Deng, R. L. Brennan. HMM-based strategies for enhancement of speech signals embedded in nonstationary noise[J]. IEEE Trans. Speech Audio Process, 1998 6 445-455.

DOI: 10.1109/89.709670

[7] M. Klein, P. Kabal. Signal subspace speech enhancement with perceptual post-filtering[J]. Proc. IEEE Internat. Conf. Acoust. Speech Signal Process. (ICASSP), 2002 1 537-540.

DOI: 10.1109/icassp.2002.1005795

[8] D. L. Donoho. De-noising by soft-thresholding[J]. IEEE Trans. Inf, 1995 41 613-627.

DOI: 10.1109/18.382009

[9] S. Li, J. Q. Wang, X. J. Jing. The Application of Nonlinear Spectral Subtraction Method on Millimeter Wave Conducted Speech Enhancement[J]. Mathematical Problems in Engineering, 2010 2010 1-12.

DOI: 10.1155/2010/371782

[10] S. Li, Y. Tian, G. Lu, Y. Zhang, H. Xue, J. Wang, X. Jing. A new kind of non-acoustic speech acquisition method based on millimeter waveradar[J]. Progress In Electromagnetics Research, 2012 130 17-40.

DOI: 10.2528/pier12052207

[11] W. Sweldens. The lifting scheme: A custom-design construction of biorthogonal wavelets[J]. Journal of Appl. And Comput. Harmonic Analysis, 1996 3 186-200.

DOI: 10.1006/acha.1996.0015

[12] Y. Huang, ChengliangLiu, XuanF. Zha, YanmingLi. An enhanced feature extraction model using lifting-based wavelet packettransform scheme and sampling-importance-resampling analysis[J]. Mechanical Systems and Signal Processing, 2009 23 2470–2487.

DOI: 10.1016/j.ymssp.2009.06.003

[13] M. Berouti, R. Schwartz, and J. Makhoul. Enhancement of speech corrupted by acoustic noise[J]. Proc. IEEE Int. Conf. Acoust., Speech Signal Processing, 1979 4 208-211.

DOI: 10.1109/icassp.1979.1170788