ICASSP 2022accepted0 citations
A Two-Step Backward Compatible Fullband Speech Enhancement System
Xu Zhang, Lianwu Chen, Xiguang Zheng, Xinlei Ren, Chen Zhang, Liang Guo, Bing Yu
Abstract
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 full-band systems that utilize perceptually motivated features to train the fullband speech enhancement with 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.
BibTeX
@inproceedings{icassp2022_atwostepbackward,
title = {A Two-Step Backward Compatible Fullband Speech Enhancement System},
author = {Xu Zhang and Lianwu Chen and Xiguang Zheng and Xinlei Ren and Chen Zhang and Liang Guo and Bing Yu},
booktitle = {ICASSP 2022},
year = {2022}
}