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Received: 2008-05-22

Revision Accepted: 2008-10-10

Crosschecked: 2009-04-27

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Journal of Zhejiang University SCIENCE A 2009 Vol.10 No.6 P.805-809

http://doi.org/10.1631/jzus.A0820390


A noise cross PSD estimator for dual-microphone speech enhancement based on minimum statistics


Author(s):  Mohsen RAHMANI, Ahmad AKBARI, Beghdad AYAD, Nima DERAKHSHAN

Affiliation(s):  Research Center for Information Technology, Computer Department, Iran University of Science and Technology, Tehran, Iran

Corresponding email(s):   m-rahmani@araku.ac.ir

Key Words:  Two-channel noise reduction, Noise estimation, Minima tracking


Mohsen RAHMANI, Ahmad AKBARI, Beghdad AYAD, Nima DERAKHSHAN. A noise cross PSD estimator for dual-microphone speech enhancement based on minimum statistics[J]. Journal of Zhejiang University Science A, 2009, 10(6): 805-809.

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Abstract: 
Some two-microphone noise reduction techniques that work in the frequency domain exploit coherence function between two noisy signals. They have shown good results when noise signals on two sensors are uncorrelated, but their performance decreases with correlated noises. Coherence based methods can be improved when the cross power spectral density (CPSD) of correlated noise signals is available. In this paper, we propose a new method for estimation of the CPSD of the noise, which is based on the minimum tracking technique. Despite the fact that the proposed estimator does not need to implement a voice activity detector (VAD), its performance is comparable to a CPSD estimator that uses an ideal VAD.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1] Cohen, I., 2002. Noise estimation by minima controlled recursive averaging for robust speech enhancement. IEEE Signal Processing Lett., 9(1):12-15.

[2] Deller, J.R., Hansen, J.H.L., Proakis, J.G., 2000. Discrete-time Processing of Speech Signals (2nd Ed.). IEEE Press, New York, USA.

[3] Derakhshan, N., Ayatollahi, A., Akbari, A., Rahmani, M., 2007. Noise Power Spectrum Estimation Using Time-variant Spectral Smoothing and Low-delay Minima Tracking. SPECOM, p.542-548.

[4] Guerin, A., La Bouquin-Jeannes, R., Faucon, G., 2003. A two-sensor noise reduction system: applications for hands-free car kit. EURASIP J. Appl. Signal Processing, 2003(11):1125-1134.

[5] ITU-T P.862, 2001. Perceptual Evaluation of Speech Quality (PESQ): An Objective Method for End-to-end Speech Quality Assessment of Narrow-band Telephone Networks and Speech Codecs. International Telecommunication Union, Geneva.

[6] La Bouquin-Jeannes, R., Azirani, A.A., Faucon, G., 1997. Enhancement of speech degraded by coherent and incoherent noise using a cross-spectral estimator. IEEE Trans. Speech Audio Processing, 5(5):484-487.

[7] Martin, R., 1994. Spectral Subtraction Based on Minimum Statistics. 7th European Signal Processing Conf., p.1182-1185.

[8] Martin, R., 2001. Noise power spectral density estimation based on optimal smoothing and minimum statistics. IEEE Trans. Speech Audio Processing, 9(5):504-512.

[9] Martin, R., 2006. Bias compensation methods for minimum statistics noise power spectral density estimation. Signal Processing, 86(6):1215-1229.

[10] Zhang, X., Jia, Y., 2005. A Soft Decision Based Noise Cross Power Spectral Density Estimation for Two-microphone Speech Enhancement Systems. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, p.813-816.

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