4 accepted papers
Deep neural network (DNN)-based approaches to acoustic echo cancellation (AEC) and hybrid speech enhancement systems have gained increasing attention recently, introducing significant performance improvements to this research field. Using the fully convolutional recurrent network (FCRN) architecture…
Acoustic echo cancellation (AEC) algorithms have a long-term steady role in signal processing, with approaches improving the performance of applications such as automotive hands-free systems, smart home and loudspeaker devices, or web conference systems. Just recently, very first deep neural network…
Acoustic feedback cancellation has gained a major and steady role in the research fields of signal processing over the past decades, since it is inevitable for numerous applications such as hearing aids or in-car communication systems. In this paper, we investigate measurement noise covariance estim…
Emerging use cases, such as keyword spotting while listening to FM radio, or participating in a teleconference utilizing the hands-free system in a vehicle, require the utilization of multi-channel acoustic echo cancellation (AEC). Addressing the typically remaining residual echo, it is common pract…