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Performance analysis of an improved split functional link adaptive filtering algorithm for nonlinear AEC
Applied Acoustics ( IF 3.4 ) Pub Date : 2021-01-01 , DOI: 10.1016/j.apacoust.2020.107863
Srikanth Burra , Asutosh Kar

In the process of nonlinear acoustic echo cancellation (NAEC), the eradication of echo becomes challenging due to the nonlinear distortion introduced by the low-cost hands-free communication devices. To mitigate the effect of these artifacts, various NAEC adaptive filtering algorithms are existing which find their applicability in different echoed environments. But, there exists a scope to improve the echo return loss enhancement (ERLE) performance and the rate of convergence for adaptive NAEC algorithms. These improvements can be achieved with further optimization of key parameters in existing mean square error based adaptive algorithms and by proposing a novel combination of linear and nonlinear adaptive filters. In this paper, a split functional link-based adaptive filter (SFLAF) is proposed with an improved optimized -normalized least mean square adaptive algorithm for NAEC. In addition to that, the convergence and steady-state analyses of the proposed algorithm were presented in this paper. The performance of the proposed algorithm is compared to existing SFLAF based NAEC algorithms, and improvements are presented. The colored noise signal, clean speech, and speech signal corrupted with white noise are subjected as inputs to the proposed NAEC framework under different signal-to-noise ratios. The ERLE, spectrograms, and perceptual evaluation of sound quality are used as the performance indices for the comparison of the proposed algorithm with its counterparts. An average improvement of 3 dB is observed in the case of the proposed algorithm compared to its counterparts.



中文翻译:

改进的非线性AEC分裂功能链接自适应滤波算法性能分析

在非线性声学回声消除(NAEC)过程中,由于低成本免提通信设备引入的非线性失真,消除回声变得具有挑战性。为了减轻这些伪影的影响,现有各种NAEC自适应滤波算法,它们在不同的回声环境中均具有适用性。但是,对于自适应NAEC算法,存在改善回波回波损耗增强(ERLE)性能和收敛速度的范围。这些改进可以通过进一步优化现有基于均方误差的自适应算法中的关键参数,以及提出线性和非线性自适应滤波器的新颖组合来实现。在本文中,提出了一种具有改进的归一化最小均方自适应NAEC算法的基于分裂功能链路的自适应滤波器(SFLAF)。除此之外,本文还对算法进行了收敛性和稳态分析。将该算法的性能与现有的基于SFLAF的NAEC算法进行了比较,并提出了改进方案。在不同的信噪比下,彩色噪声信号,干净的语音和被白噪声破坏的语音信号将作为提议的NAEC框架的输入。ERLE,声谱图和声音质量的感知评估被用作性能指标,用于将所提出的算法与其对应的算法进行比较。与相应算法相比,在所提出算法的情况下观察到平均改善3 dB。

更新日期:2021-01-01
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