The ICASSP 2023 Acoustic Echo Cancellation Challenge is intended to stimulate research
in acoustic echo cancellation (AEC), which is an important area of speech enhancement and …

The ICASSP 2021 Acoustic Echo Cancellation Challenge is intended to stimulate research
in the area of acoustic echo cancellation (AEC), which is an important part of speech …

Abstract The INTERSPEECH 2021 Acoustic Echo Cancellation Challenge is intended to
stimulate research in the area of acoustic echo cancellation (AEC), which is an important …

This paper applies the dual-signal transformation LSTM network (DTLN) to the task of real-
time acoustic echo cancellation (AEC). The DTLN combines a short-time Fourier transform …

Traditionally, the quality of acoustic echo cancellers is evaluated using intrusive speech
quality assessment measures such as ERLE [1] and PESQ [2], or by carrying out subjective …

With the increasing demand for audio communication and online conference, ensuring the
robustness of Acoustic Echo Cancellation (AEC) under the complicated acoustic scenario …

In this contribution, we introduce a novel approach to noise-robust acoustic echo
cancellation employing a complex-valued Deep Neural Network (DNN) for postfiltering. In a …

This paper presents a real-time Acoustic Echo Cancellation (AEC) algorithm submitted to the
AEC-Challenge. The algorithm consists of three modules: Generalized Cross-Correlation …

The Kalman filter has been adopted in acoustic echo cancellation due to its robustness to
double-talk, fast convergence, and good steady-state performance. The performance of …

In this paper, we propose a residual echo suppression method using a UNet neural network
that directly maps the outputs of a linear acoustic echo canceler to the desired signal in the …