Title: Optimal design of minimum mean-square error noise reduction algorithms using the simulated annealing technique
Authors: Bai, Mingsian R.
Hsieh, Ping-Ju
Hur, Kur-Nan
機械工程學系
Department of Mechanical Engineering
Issue Date: 1-Feb-2009
Abstract: The performance of the minimum mean-square error noise reduction (MMSE-NR) algorithm in conjunction with time-recursive averaging (TRA) for noise estimation is found to be very sensitive to the choice of two recursion parameters. To address this problem in a more systematic manner, this paper proposes an optimization method to efficiently search the optimal parameters of the MMSE-TRA-NR algorithms. The objective function is based on a regression model, whereas the optimization process is carried out with the simulated annealing algorithm that is well suited for problems with many local optima. Another NR algorithm proposed in the paper employs linear prediction coding as a preprocessor for extracting the correlated portion of human speech. Objective and subjective tests were undertaken to compare the optimized MMSE-TRA-NR algorithm with several conventional NR algorithms. The results of subjective tests were processed by using analysis of variance to justify the statistic significance. A post hoc test, Tukey's Honestly Significant Difference, was conducted to further assess the pairwise difference between the NR algorithms. (C) 2009 Acoustical Society of America. [DOI: 10.1121/1.3050292]
URI: http://dx.doi.org/10.1121/1.3050292
http://hdl.handle.net/11536/7702
ISSN: 0001-4966
DOI: 10.1121/1.3050292
Journal: JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA
Volume: 125
Issue: 2
Begin Page: 934
End Page: 943
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