2014Unpublished venueRequires access

Speech enhancement based on combination of wiener filter and subspace filter

Yousheng Xia, Huang Jian-Wen

Open publisher page 11 citations

Abstract

This paper propose a novel multi-channel speech enhancement method by combining the wiener filtering and subspace filtering with a convex combinational coefficient. Because of using both the advantage in noise reduction of the subspace speech enhancement technology and the stable characteristic of the Wiener filtering technology, the proposed multi-channel speech enhancement method has a better performance in robustly removing colored noise from noisy speech signals. Simulation examples confirm that under different colored noise, the proposed multi-channel speech enhancement method can obtain better speech recovery results than the traditional subspace multi-channel speech enhancement method and the multi-channel Wiener filter speech enhancement method.

About this research paper

What this paper is about

This paper propose a novel multi-channel speech enhancement method by combining the wiener filtering and subspace filtering with a convex combinational coefficient. Because of using both the advantage in noise reduction of the subspace speech enhancement technology and the stable characteristic of the Wiener filtering technology, the proposed multi-channel speech enhancement method has a better performance in robustly removing colored noise from noisy speech signals. Simulation examples confirm that under different colored noise, the proposed multi-channel speech enhancement method can obtain better speech recovery results than the traditional subspace multi-channel speech enhancement method and the multi-channel Wiener filter speech enhancement method.

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OpenAlex reports 11 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Method / approach

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Available abstract

This paper propose a novel multi-channel speech enhancement method by combining the wiener filtering and subspace filtering with a convex combinational coefficient. Because of using both the advantage in noise reduction of the subspace speech enhancement technology and the stable characteristic of the Wiener filtering technology, the proposed multi-channel speech enhancement method has a better performance in robustly removing colored noise from noisy speech signals. Simulation examples confirm that under different colored noise, the proposed multi-channel speech enhancement method can obtain better speech recovery results than the traditional subspace multi-channel speech enhancement method and the multi-channel Wiener filter speech enhancement method.

Key concepts: Speech enhancement, Wiener filter, Speech recognition, Subspace topology, Computer science, Filter (signal processing), Colors of noise, Wiener deconvolution

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