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A new adaptive filtering subband algorithm for two-channel acoustic noise reduction and speech enhancement

机译:一种新的自适应滤波子带算法,用于双通道降噪和语音增强

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This paper addresses the problem of acoustic noise reduction and speech enhancement by adaptive filtering algorithms. Most speech enhancement methods and algorithms which use adaptive filtering structure are generally expressed in fullband form. One of these widespread structures is the Forward Blind Source Separation Structure (FBSS). This FBSS structure is often used to separate speech form noise and therefore enhance the speech signal at the processing output. In this paper, we propose a new subband implementation of this FBSS structure. In order to give more robustness to the proposed structure, we adapt then we apply to this subband structure a new combination of criteria based on the system mismatch and the smoothing filtering errors minimizations. The combination between this proposed subband structure with this optimal criteria allows to obtain a new two-channel subband forward (2CSF) algorithm that improves the convergence speed of the cross adaptive filters which are used to separate speech from noise. Objective tests under various environments are presented showing the good behavior of the proposed 2CSF algorithm.
机译:本文通过自适应滤波算法解决了声学降噪和语音增强的问题。大多数使用自适应滤波结构的语音增强方法和算法通常以全频带形式表示。这些广泛使用的结构之一是前向盲源分离结构(FBSS)。这种FBSS结构通常用于分离语音形式的噪声,因此可以增强处理输出端的语音信号。在本文中,我们提出了该FBSS结构的新子带实现。为了使所提出的结构具有更高的鲁棒性,我们进行调整,然后将基于系统失配和平滑滤波误差最小化的准则的新组合应用于该子带结构。所提出的子带结构与该最佳准则之间的组合允许获得新的两通道子带正向(2CSF)算法,该算法可提高用于将语音与噪声分离的交叉自适应滤波器的收敛速度。提出了在各种环境下的客观测试,表明了所提出的2CSF算法的良好性能。

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