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Noise Cancellation Algorithm of Bone Conduction Speech Signal using Feature of Noise in Separated Band
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 Title & Authors
Noise Cancellation Algorithm of Bone Conduction Speech Signal using Feature of Noise in Separated Band
Lee, Jina; Lee, Gihyoun; Na, Sung Dae; Seong, Ki Woong; Cho, Jin Ho; Kim, Myoung Nam;
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 Abstract
In mobile communication, air conduction(AC) speech signal had been commonly used, but it was easily affected by ambient noise environment such as emergency, military action and rescue. To overcome the weakness of the AC speech signal, bone conduction(BC) speech signal have been used. The BC speech signal is transmitted through bone vibration, so it is affected less by the background noise. In this paper, we proposed noise cancellation algorithm of the BC speech signal using noise feature of decomposed bands. The proposed algorithm consist of three steps. First, the BC speech signal is divided into 17 bands using perceptual wavelet packet decomposition. Second, threshold is calculated by noise feature during short time of separated-band and compared to absolute average of the signal frame. Therefore, the speech and noise parts are detected. Last, the detected noise parts are removed and then, noise eliminated bands are re-synthesised. In order to confirm the efficiency of the proposed algorithm, we compared the proposed algorithm with conventional algorithm. And the proposed algorithm has better performance than the conventional algorithm.
 Keywords
Noise Cancellation;Bone Conduction Speech Signal;Perceptual Wavelet Packet Decomposition;
 Language
Korean
 Cited by
 References
1.
T. Dekens and W. Verhelst, “Body Conducted Speech Enhancement by Equalization and Signal Fusion,” IEEE Transactions on Audio, Speech, and Language Processing, Vol. 21, No. 12, pp. 2481-2492, 2013. crossref(new window)

2.
H.S. Shin, H. Kang, and T. Fingscheidt, "Survey of Speech Enhancement Supported by a Bone Conduction Microphone," Proceeding of ITG Symposium Proceedings of Speech Communication, pp. 1-4, 2012.

3.
M.S. Rahman, A. Saha, and T. Shimamura, "Low-Frequency Band Noise Suppression Using Bone Conducted Speech," Proceeding of IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, pp. 520-525, 2011.

4.
Y. Xiao, R. Xiao, B. Huang, and K. Hasegawa, "A Nonlinear Adaptive Noise Canceller for Speech Enhancement Using Volterra Filter," Proceeding of International Conference on Advanced Mechatronic Systems, pp. 204-208, 2014.

5.
B. Huang, Y. Xiao, J. Sun, G. Wei, and H. Wei, "Speech Enhancement Based on FLANN Using Both Bone- and Air-conducted Measurements," Proceeding of Annual Summit and Conference on Asia-Pacific Signal and Information Processing Association, pp. 1-5, 2014.

6.
M. Zhu, H. Ji, F. Luo, and W. Chen, "A Robust Speech Enhancement Scheme on the Basis of Bone-conductive Microphones," Proceeding of International Workshop on Signal Design and I ts Applications in Communications, pp. 23-27, 2007.

7.
Z. Kong, Y. Liu, K. Liu, and M. Jiang, "An Improved Design for Speech Denoising," Proceeding of International Symposium on Communications and Information Techonologies, pp. 141-144, 2008.

8.
S.D. Kamath and P.C. Loizou, "A Multi-band Spectral Subtraction Method for Enhancing Speech Corrupted by Colored Noise," Proceeding of IEEE International Conference on Acoustic, Speech, and Signal Processing, pp. 4164, 2002.

9.
R. Campbell, B. Dodd, and D. Burnham, Hearing by Eye Ⅱ: Advances in the Psychology of Speechreading and Auditory-visual Speech, Psychology Press Ltd, Publishers, East Sussex, 1998.

10.
H.W. Park, W.S. Lim, and M.J. Bae, “The Voice Quality Improvement by Bone Conduction Feedback Compensation in Mobile Phone,” The Journal of the Acoustical Society of Korea, Vol. 31, No. 6, pp. 359-366, 2012. crossref(new window)

11.
J. Kwak, Y. Lee, and S. Ahn, "Improved Speech Enhancement Using Multi-Band Power Subtraction and Perceptual Wavelet Packet Decomposition," Proceeding of Korean Institute of Communications and Information Sciences, pp. 171-174, 2005.

12.
G.H. Lee, Y.J. Lee, and M.N. Kim, “Voice Activity Detection Algorithm Using Wavelet Band Entropy Ensemble Analysis in Car Noisy Environments,” Journal of Korea Multimedia Society, Vol. 16, No. 9, pp. 1105-1017, 2013.

13.
Y. Lee, J. Kwak, and S. Ahn, “Improved Speech Enhancement Algorithm Employing Multi-Band Power Subtraction and Wavelet Packet Decomposition,” The Journal of Korean Institute of Communications and Information Sciences, Vol. 31, No. 6C, pp. 589-602, 2006.