Nonlinear Residual Echo Suppression Based on Multi-stream Conv-TasNet
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
ICASSP 2023 Acoustic Echo Cancellation Challenge
End-To-End Deep Learning-based Adaptation Control for Linear Acoustic Echo Cancellation
Low-Complexity Acoustic Echo Cancellation with Neural Kalman Filtering
Semi-blind source separation using convolutive transfer function for nonlinear acoustic echo cancellation
Joint Acoustic Echo Cancellation and Blind Source Extraction based on Independent Vector Extraction
ICASSP 2022 Acoustic Echo Cancellation Challenge
토론
이 논문과 연결된 포럼 글이 아직 없습니다.