Efficient Nonlinear Acoustic Echo Cancellation by Dual-stage Multi-channel Kalman Filtering

2019 
Mobile devices for hands-free speech communication often show significant nonlinear distortion in the sound emitted by their loudspeakers. Therefore, conventional linear echo cancellation is not sufficient for maintaining a high conversation quality. In this work we propose a nonlinear echo canceller that uses two serially cascaded adaptive filters to compensate for the nonlinear and linear echo. We show that a stable operation of the cascaded structure is achieved by using the multi-channel Kalman algorithm in the frequency domain with filtered-x references. By modelling a nonlinearity with memory we further improve the performance. To reduce the computational complexity of the proposed solution we derive an efficient decimation scheme by exploiting useful properties of the cascaded approach.
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