  Speech enhancement methods based on deep learning have surpassed traditional
methods. While many of these new approaches are operating on the wideband
(16kHz) sample rate, a new fullband (48kHz) speech enhancement system is
proposed in this paper. Compared to the existing fullband systems that utilizes
perceptually motivated features to train the fullband speech enhancement using
a single network structure, the proposed system is a two-step system ensuring
good fullband speech enhancement quality while backward compatible to the
existing wideband systems.
