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A new efficient two-channel fast transversal adaptive filtering algorithm for blind speech enhancement and acoustic noise reduction

机译:一种新的高效双通道快速横向自适应滤波算法,用于盲语言增强和声噪声降低

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This paper addresses the problem of speech enhancement and acoustic noise reduction by blind structures. Recently, the backward blind source separation (BBSS) structure has shown efficiency in cancelling the acoustic noise and improving corrupted speech signals form very noisy observations without any a priori information of source signals. In this paper, we propose a new algorithm based on the combination between the BBSS structure and the simplified fast transversal filter (SFTF) algorithm. The proposed two-channel simplified fast transversal filter (TCSFTF) algorithm succeeded an important blind improvement of steady state and convergence speed performances in diverse noisy situations when only the noisy signals are known. The performances of the new TCSFTF algorithm are compared with four state-of-the-art algorithms in different noisy conditions. This comparison is evaluated in terms of cepstral distance (CD), system mismatch (SM), segmental signal to noise ratio (SegSNR), and segmental mean square error (SegMSE) criteria. (C) 2018 Elsevier Ltd. All rights reserved.
机译:本文通过盲结构解决了语音增强和声噪声降低的问题。最近,后向盲源分离(BBS)结构在取消声学噪声并改善损坏的语音信号方面具有非常嘈杂的观察的效率,而没有任何先验的源信号。在本文中,我们提出了一种基于BBSS结构与简化快速横向滤波器(SFTF)算法的组合的新算法。所提出的双通道简化的快速横向滤波器(TCSFTF)算法在仅知道噪声信号时,在不同噪声情况下,在不同噪声情况下的稳态和收敛速度表现的重要盲目提高。将新的TCSFTF算法的性能与不同嘈杂的条件中的四个最新算法进行了比较。在临时距离(CD),系统失配(SM),节段信号到噪声比(SEGSNR)和分段均方误差(SEGMSE)标准方面评估该比较。 (c)2018年elestvier有限公司保留所有权利。

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