基于gevd的分布式自适应节点特定信号估计与先验知识的分布式组合声回波抵消与降噪

Santiago Ruiz, T. Waterschoot, M. Moonen
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引用次数: 1

摘要

使用特定版本的PK-GEVD-DANSE算法(cfr)解决了无线声传感器网络(nn)中的分布式联合声回波抵消(AEC)和降噪(NR)问题。[1])。虽然该算法最初是针对具有部分先验知识的期望语音转向向量的分布式NR开发的,但研究表明,它也可以用于与NR结合的AEC。使用集中式和分布式批处理模式进行了仿真,以验证该算法在用回波回波损耗增强(ERLE)量化的AEC方面的性能,以及用信噪比(SNR)量化的NR方面的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed combined acoustic echo cancellation and noise reduction using GEVD-based distributed adaptive node specific signal estimation with prior knowledge
Distributed combined acoustic echo cancellation (AEC) and noise reduction (NR) in a wireless acoustic sensor network (WASN) is tackled by using a specific version of the PK-GEVD-DANSE algorithm (cfr. [1]). Although this algorithm was initially developed for distributed NR with partial prior knowledge of the desired speech steering vector, it is shown that it can also be used for AEC combined with NR. Simulations have been carried out using centralized and distributed batch-mode implementations to verify the performance of the algorithm in terms of AEC quantified with the echo return loss enhancement (ERLE), as well as in terms of the NR quantified with the signal- to-noise ratio (SNR).
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