A Non-Contact Speech Enhancement Algorithm Based on Wavelet Packet Adaptive Threshold

Hui Jun Xue; Sheng Li; Teng Jiao; Guo Hua Lu; Yang Zhang; Jian Qi Wang; Xi Jing Jing

doi:10.4028/www.scientific.net/AMM.241-244.194

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 241-244A Non-Contact Speech Enhancement Algorithm Based...

A Non-Contact Speech Enhancement Algorithm Based on Wavelet Packet Adaptive Threshold

Abstract:

Speech is an important method for human communication. In this paper, we developed a new method for detecting speech signal. Because of the advantage of this speech detecting method, it has great potential application value in many fields. Simultaneously, basing on the good capability of wavelet packet for analyzing time-frequency signal, this paper also developed an algorithm of wavelet packet threshold by using hard threshold and soft threshold for removing noise. Comparing to spectral subtraction and Wiener filter speech enhancement algorithm, the proposed algorithm takes on a better performance on noise removing and speech signal reserving.

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Periodical:

Applied Mechanics and Materials (Volumes 241-244)

Pages:

194-198

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.241-244.194

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Online since:

December 2012

Authors:

Hui Jun Xue*, Sheng Li, Teng Jiao, Guo Hua Lu, Yang Zhang, Jian Qi Wang, Xi Jing Jing

Keywords:

Non-Contact Speech, Spectrogram, Threshold, Wavelet Packet

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References

[1] Z. W. Li, Millimeter wave radar for detecting the speech signal applications, J. Int.J.InfraredMill Wave. 17 (1996) 2175-2183.

DOI: 10.1007/bf02069493

Google Scholar

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

DOI: 10.1121/1.421133

Google Scholar

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

DOI: 10.1109/tassp.1979.1163209

Google Scholar

[4] 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. 6(1998) 445-455.

DOI: 10.1109/89.709670

Google Scholar

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

DOI: 10.1109/icassp.2002.1005795

Google Scholar

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

DOI: 10.1109/18.382009

Google Scholar

[7] 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

Google Scholar

[8] 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. 50 (2008) 2109–2114.

DOI: 10.1002/mop.23588

Google Scholar

[9] M. Berouti, R. Schwartz, J. Makhoul, Enhancement of speech corrupted by acoustic noise, J.In: Proc. IEEE Internat.Conf. on Acoust. Speech Signal Process. (ICASSP).(1979) 208-211.

DOI: 10.1109/icassp.1979.1170788

Google Scholar