EXAMPLES OF OPTIMAL NOISE REDUCTION FILTERS DERIVED FROM THE SQUARED PEARSON CORRELATION COEFFICIENT

被引：0

作者：

Yu, Jiaolong ^{[1
]}

Benesty, Jacob

Huang, Gongping ^{[1
]}

Chen, Jingdong ^{[1
]}

机构：

[1] Northwestern Polytech Univ, 127 Youyi West Rd, Xian 710072, Shaanxi, Peoples R China

来源：

2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2014年

关键词：

Noise reduction; speech enhancement; squared Pearson correlation coefficient (SPCC); optimal filters; SPECTRAL AMPLITUDE ESTIMATOR; SPEECH ENHANCEMENT; COLORED NOISE; SUPPRESSION;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper studies the problem of single-channel noise reduction in the time domain. Based on some orthogonal decomposition developed recently and the squared Pearson correlation coefficient (SPCC), several noise reduction filters are derived. We will show that the optimization of the SPCC leads to the Wiener, minimum variance distortionless response (MVDR), minimum noise (MN), minimum uncorrelated speech and noise (MUSN), and linearly constrained minimum variance (LCMV) filters. We also compare the Wiener and MVDR filters derived from the SPCC to their counterparts derived from the mean-square error (MSE) criterion. Simulations are provided to illustrate the performance of all the deduced noise reduction filters.

引用

页数：5

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