@inproceedings{103e8ade168b4e58817e7ae317fe4de9,
title = "Bs-Plcnet: Band-Split Packet Loss Concealment Network with Multi-Task Learning Framework and Multi-Discriminators",
abstract = "Packet loss is a common and unavoidable problem in voice over internet phone (VoIP) systems. To deal with the problem, we propose a band-split packet loss concealment network (BS-PLCNet). Specifically, we split the full-band signal into wide-band (0-8kHz) and high-band (8-24kHz). The wide-band signals are processed by a gated convolutional recurrent network (GCRN), while the high-band counterpart is processed by a simple GRU network. To ensure high speech quality and automatic speech recognition (ASR) compatibility, multi-task learning (MTL) framework including fundamental frequency (f0) prediction, linguistic awareness, and multi-discriminators are used. The proposed approach tied for 1st place in the ICASSP 2024 PLC Challenge.",
keywords = "Packet loss concealment, band split, generative adversarial network, multi-task learning",
author = "Zihan Zhang and Jiayao Sun and Xianjun Xia and Chuanzeng Huang and Yijian Xiao and Lei Xie",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops, ICASSPW 2024 ; Conference date: 14-04-2024 Through 19-04-2024",
year = "2024",
doi = "10.1109/ICASSPW62465.2024.10627343",
language = "英语",
series = "2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops, ICASSPW 2024 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "23--24",
booktitle = "2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops, ICASSPW 2024 - Proceedings",
}