论文标题

基于多流conv-tasnet的非线性残留回声抑制

Nonlinear Residual Echo Suppression Based on Multi-stream Conv-TasNet

论文作者

Chen, Hongsheng, Xiang, Teng, Chen, Kai, Lu, Jing

论文摘要

由于回声和远端信号之间的非线性关系,无法通过线性自适应过滤器完全删除声音回声。通常需要一个后处理模块来进一步抑制回声。在本文中,我们提出了一种基于完全卷积的时间域音频分离网络(Conv-TASNET)的修改的残留回声抑制方法。线性声音回声取消系统的残差信号和自适应滤波器的输出都被采用以形成conv-tasnet的多个流,从而导致更有效的回声抑制,同时保持整个系统的延迟较低。仿真结果验证了所提出的方法在单聊和双对词情况下的疗效。

Acoustic echo cannot be entirely removed by linear adaptive filters due to the nonlinear relationship between the echo and far-end signal. Usually a post processing module is required to further suppress the echo. In this paper, we propose a residual echo suppression method based on the modification of fully convolutional time-domain audio separation network (Conv-TasNet). Both the residual signal of the linear acoustic echo cancellation system, and the output of the adaptive filter are adopted to form multiple streams for the Conv-TasNet, resulting in more effective echo suppression while keeping a lower latency of the whole system. Simulation results validate the efficacy of the proposed method in both single-talk and double-talk situations.

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