Document Detail


Single-channel noise reduction using optimal rectangular filtering matrices.
MedLine Citation:
PMID:  23363124     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
This paper studies the problem of single-channel noise reduction in the time domain and presents a block-based approach where a vector of the desired speech signal is recovered by filtering a frame of the noisy signal with a rectangular filtering matrix. With this formulation, the noise reduction problem becomes one of estimating an optimal filtering matrix. To achieve such estimation, a method is introduced to decompose a frame of the clean speech signal into two orthogonal components: One correlated and the other uncorrelated with the current desired speech vector to be estimated. Different optimization cost functions are then formulated from which non-causal optimal filtering matrices are derived. The relationships among these optimal filtering matrices are discussed. In comparison with the classical sample-based technique that uses only forward prediction, the block-based method presented in this paper exploits both the forward and backward prediction as well as the temporal interpolation and, therefore, can improve the noise reduction performance by fully taking advantage of the speech property of self correlation. There is also a side advantage of this block-based method as compared to the sample-based technique, i.e., it is computationally more efficient and, as a result, more suitable for practical implementation.
Authors:
Tao Long; Jingdong Chen; Jacob Benesty; Zhenxi Zhang
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  The Journal of the Acoustical Society of America     Volume:  133     ISSN:  1520-8524     ISO Abbreviation:  J. Acoust. Soc. Am.     Publication Date:  2013 Feb 
Date Detail:
Created Date:  2013-01-31     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7503051     Medline TA:  J Acoust Soc Am     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1090-101     Citation Subset:  IM    
Affiliation:
Key Laboratory of Biomedical Information Engineering of Education Ministry, Institute of Biomedical Analytical Technology and Instrumentation, Xi'an Jiaotong University, 28 Xianning West Road, Xi'an, Shaanxi 710049, China.
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