Acoustic Echo Cancellation Using Deep Cerebellar Model Articulation Controller

2017 FIFTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS(2017)

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摘要
In this paper, we propose to adopt the deep cerebellar model articulation controller (DCMAC) model for acoustic echo cancellation (AEC). The DCMAC model is formed by stacking multiple CMAC models. The deep structure of the DCMAC model can characterize nonlinear transformations more effectively when compared with the conventional CMAC model. Experimental results showed that DCMAC outperforms CMAC in terms of MSE values, confirming that DCMAC yields improved capability of modeling channel characteristics.
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关键词
cerebellar model articulation controller, deep learning, adaptive noise cancellation
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