Study On Efficient Adaptive Filtering Algorithms For Advanced AEC Problems

Acoustic Echo Cancellation(AEC)technology is widely used in hands-free communication,which makes it possible for both parties to cancel the interference caused by the echo during the conversation without holding the terminal equipment.Due to the diversification and complexity of the application of AEC technology,the traditional single-channel linear AEC becomes unable to meet the market's demands.Stereophonic Acoustic Echo Cancellation(SAEC)and Nonlinear Acoustic Echo Cancellation(NLAEC)are two advanced AEC technologies.This thesis focuses on the robustness,computational complexity,and steady-state convergence of adaptive filtering algorithms,which are the cores of the dual-path adaptive filtering algorithm for SAEC and kernel adaptive filtering algorithm applied to NLAEC.The thesis is organized as follows:Firstly,aiming at the double-talk and echo path change that often appear in the SAEC scenario,this thesis proposed a dual-channel dual-path frequency domain algorithm.Different from the traditional ELMS algorithm,which utilizes one filter to track each echo path,a double filter structure is applied in the proposed algorithm to track an echo path simultaneously through a continuously updated background filter and a non-auto-updating foreground filter so as to improve the robustness of the algorithm in high interference environments.The algorithm tracks the echo path continuously through the background filter,and the transition logic controls it to transfer the tap coefficients to the foreground filter in a high-interference environment to output the steady-state error.This method not only solves the problem that the adaptive filter is easy to diverge during double-talk,but also overcomes the problem of filter coefficients freezing caused by the misjudgment of traditional double talk detection(DTD)when the echo path suddenly changes.Next,the proposed dual-path frequency domain algorithm is transplanted to the AEC module of WebRTC platform,realize and validate the engineering application of this algorithm.Secondly,aiming to achieve optimal configuration of the computational complexity and convergence speed,a switching adaptive kernel adaptive filter switching algorithm for NLAEC is proposed.The algorithm first utilizes a voice activity detection(VAD)technique based on the fast and slow envelope detection to discriminate the different energy of the speech segments,and then calculates the energy threshold by using the difference between fast envelope and slow envelope.The switching mechanism is employed to switch different modes of the kernel adaptive algorithm.The switched kernel adaptive algorithm not only has the ability to estimate and model the nonlinear acoustic echo channel which traditional linear adaptive filtering algorithms do not have,but also introduces a switching mechanism that can well balance the convergence speed and computational complexity.It is a suitable solution for NLAEC engineering implementation.