This paper presents a multiple sub-filter-based improved nonlinear acoustic echo cancellation (NAEC) framework to enhance the echo cancellation performance of the NAEC in the presence of nonlinear distortion. The proposed algorithm uses a novel combination of adaptive multiple sub-filter approach and proportionate filtering to enhance the convergence rate of the existing proportionate functional link-based NAEC algorithm by reducing the adaption time needed for updating the coefficients of the adaptive filter. In addition to that, the convergence and the steady-state analysis of the proposed algorithm are presented. The proposed NAEC framework is subjected to speech signal input corrupted with both white as well as colored noise as background noise and the colored noise input at low-to–high SNR conditions for a comprehensive analysis of the echo cancellation performance. The experimental results comprising of the echo return loss enhancement, spectrograms, and the perceptual evaluation of speech quality demonstrate the improvements brought by the proposed algorithm. At all signal-to-noise ratio conditions, the proposed algorithm has shown a 4 dB improvement in mean echo return loss enhancement compared to the existing algorithms validating the improvement in the proposed NAEC scheme’s performance.

本文提出了一种基于多子滤波器的改进非线性声学回声消除 (NAEC) 框架，以在存在非线性失真的情况下增强 NAEC 的回声消除性能。所提出的算法使用自适应多子滤波器方法和比例滤波的新颖组合，通过减少更新自适应滤波器系数所需的适应时间来提高现有的基于比例函数链接的NAEC算法的收敛速度。除此之外，还介绍了所提出算法的收敛性和稳态分析。所提出的 NAEC 框架在低到高 SNR 条件下接受白噪声和有色噪声作为背景噪声和有色噪声输入破坏的语音信号输入，以全面分析回声消除性能。包括回声回波损耗增强、频谱图和语音质量感知评估的实验结果证明了该算法带来的改进。在所有信噪比条件下，与验证所提出的 NAEC 方案性能改进的现有算法相比，所提出的算法在平均回波回波损耗增强方面显示了 4 dB 的改进。语音质量的感知评价证明了该算法带来的改进。在所有信噪比条件下，与验证所提出的 NAEC 方案性能改进的现有算法相比，所提出的算法在平均回波回波损耗增强方面显示了 4 dB 的改进。语音质量的感知评价证明了该算法带来的改进。在所有信噪比条件下，与验证所提出的 NAEC 方案性能改进的现有算法相比，所提出的算法在平均回波回波损耗增强方面显示了 4 dB 的改进。