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A two-sensor Gauss-Seidel fast affine projection algorithm for speech enhancement and acoustic noise reduction

机译:用于语音增强和声学降噪的两传感器高斯-赛德尔快速仿射投影算法

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摘要

This paper deals with the problem of noise reduction and speech enhancement by adaptive filtering using two-sensor configuration. The well-known Gauss-Seidel fast affine projection (GSFAP) algorithm is used in various applications such as acoustic echo cancelation (AEC), and adaptive noise control. In this paper, we use the GSFAP algorithm in noise reduction and speech enhancement application. Moreover, we derive a new two-sensor GSFAP (TS-GSFAP) algorithm for speech enhancement and acoustic noise reduction application. The application of the proposed TS-GSFAP algorithm to the forward blind source separation (FBSS) structure leads to a significant improvement of the output speech signals quality even in noisy conditions. A fair comparison of the proposed TS-GSFAP algorithm with other standard two-sensor type algorithms is presented. This comparison is based on the evaluation of several objective and subjective criteria such as: the segmental signal-to-noise ratio (SegSNR), the Cepstral distance (CD) and the system mismatch (SM), the perceptual evaluation of speech quality (PESQ), and the mean opinion score (MOS) criteria. The obtained results show the good performances of the proposed TS-GSFAP algorithm. (C) 2015 Elsevier Ltd. All rights reserved.
机译:本文通过使用两传感器配置的自适应滤波来解决降噪和语音增强的问题。众所周知的高斯-赛德尔快速仿射投影(GSFAP)算法在各种应用中使用,例如回声消除(AEC)和自适应噪声控制。在本文中,我们将GSFAP算法用于降噪和语音增强应用中。此外,我们推导了一种新的两传感器GSFAP(TS-GSFAP)算法,用于语音增强和声学降噪应用。所提出的TS-GSFAP算法在前向盲源分离(FBSS)结构中的应用即使在嘈杂的条件下也可以显着提高输出语音信号的质量。提出的TS-GSFAP算法与其他标准的两传感器类型算法的公平比较。该比较基于对几个客观和主观标准的评估,例如:分段信噪比(SegSNR),倒谱距离(CD)和系统失配(SM),语音质量的感知评估(PESQ) ),以及平均意见得分(MOS)标准。获得的结果表明了所提出的TS-GSFAP算法的良好性能。 (C)2015 Elsevier Ltd.保留所有权利。

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