Single-channel noise reduction via semi-orthogonal transformations and reduced-rank filtering
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- 作者：Wei Zhang ; a ; weizhang@mail.nwpu.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Jacob Benestyb ; benesty@emt.inrs.ca" class="auth_mail" title="E-mail the corresponding author ; Jingdong Chena ; jingdongchen@ieee.org" class="auth_mail" title="E-mail the corresponding author
- 关键词：Noise reduction ; Speech enhancement ; Semi-orthogonal transformation ; Wiener filter ; MVDR filter ; Reduced-rank filter
- 刊名：Speech Communication
- 出版年：2016
- 出版时间：April 2016
- 年：2016
- 卷：78
- 期：Complete
- 页码：73-83
- 全文大小：3631 K
文摘
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A general framework is developed that combines semi-orthogonal transformation and reduced-rank filtering for noise reduction.
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Under this new framework, several optimal reduced-rank filters are derived, including the maximum SNR, the Wiener, the tradeoff, and the MVDR filters.
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Discussions are also provided on how to derive different semi-orthogonal transformations under four estimation criteria, including minimum correlation, minimum MSE, minimum distortion, and minimum residual noise.
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Simulations are performed and the results show the properties of the deduced optimal reduced-rank filters.