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Nonlinear Acoustic Echo Cancellation Based on a Sliding-Window Leaky Kernel Affine Projection Algorithm

机译:基于滑动窗口泄漏核仿射投影算法的非线性回声抵消

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摘要

Acoustic echo cancellation (AEC) is used in speech communication systems where the existence of echoes degrades the speech intelligibility. Standard approaches to AEC rely on the assumption that the echo path to be identified can be modeled by a linear filter. However, some elements introduce nonlinear distortion and must be modeled as nonlinear systems. Several nonlinear models have been used with more or less success. The kernel affine projection algorithm (KAPA) has been successfully applied to many areas in signal processing but not yet to nonlinear AEC (NLAEC). The contribution of this paper is three-fold: (1) to apply KAPA to the NLAEC problem, (2) to develop a sliding-window leaky KAPA (SWL-KAPA) that is well suited for NLAEC applications, and (3) to propose a kernel function, consisting of a weighted sum of a linear and a Gaussian kernel. In our experiment set-up, the proposed SWL-KAPA for NLAEC consistently outperforms the linear APA, resulting in up to 12 dB of improvement in ERLE at a computational cost that is only 4.6 times higher. Moreover, it is shown that the SWL-KAPA outperforms, by 4–6 dB, a Volterra-based NLAEC, which itself has a much higher 413 times computational cost than the linear APA.
机译:回声消除(AEC)用于语音通信系统,其中回声的存在会降低语音清晰度。 AEC的标准方法依赖于这样的假设,即可以通过线性滤波器对要识别的回波路径进行建模。但是,某些元素会引入非线性失真,因此必须将其建模为非线性系统。已经使用了几种非线性模型,或多或少取得了成功。内核仿射投影算法(KAPA)已成功应用于信号处理的许多领域,但尚未应用于非线性AEC(NLAEC)。本文的贡献包括三个方面:(1)将KAPA应用于NLAEC问题;(2)开发非常适合NLAEC应用的滑窗泄漏KAPA(SWL-KAPA);以及(3)提出一个核函数,它由线性核和高斯核的加权和组成。在我们的实验设置中,针对NLAEC提出的SWL-KAPA始终优于线性APA,从而以仅4.6倍的高计算成本实现了ERLE最高12 dB的改善。此外,结果表明,SWL-KAPA的性能比基于Volterra的NLAEC高出4–6 dB,后者本身的计算成本比线性APA高413倍。

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