对比两种语音降噪与回声消除算法，发现一者降噪更强，另一者回声消除更稳。
A Comparative Analysis of Generalised Echo and Interference Cancelling and Extended Multichannel Wiener Filtering for Combined Noise Reduction and Acoustic Echo Cancellation
- 用广义巴斯安分解建模非线性回声路径，改进算法适应性
- 仿真验证MWFext降噪性能更优，GEIC回声消除更鲁棒
- 适用于对回声或噪声处理有侧重需求的语音系统设计
本文分析了两种联合实现声学回声消除（AEC）与降噪（NR）的算法：广义回声与干扰抵消器（GEIC）和扩展多通道维纳滤波器（MWFext）。此前研究仅针对线性回声路径，并假设可获得独立检测目标语音与回声活动的语音活动检测器（VAD），但实际VAD可能引入误检。本文将分析拓展至：1）通过广义巴斯安分解建模一般非线性回声路径；2）在每种算法中建模VAD误差影响，从而支持特定VAD假设的分析。仿真结果表明，总体上MWFext具有更高的降噪性能，而GEIC在回声消除方面表现更鲁棒。
原文摘要 · Abstract (English)
Two algorithms for combined acoustic echo cancellation (AEC) and noise reduction (NR) are analysed, namely the generalised echo and interference canceller (GEIC) and the extended multichannel Wiener filter (MWFext). Previously, these algorithms have been examined for linear echo paths, and assuming access to voice activity detectors (VADs) that separately detect desired speech and echo activity. However, algorithms implementing VADs may introduce detection errors. Therefore, in this paper, the previous analyses are extended by 1) modelling general nonlinear echo paths by means of the generalised Bussgang decomposition, and 2) modelling VAD error effects in each specific algorithm, thereby also allowing to model specific VAD assumptions. It is found and verified with simulations that, generally, the MWFext achieves a higher NR performance, while the GEIC achieves a more robust AEC performance.
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