BS-PLCNet: Band-split Packet Loss Concealment Network with Multi-task Learning Framework and Multi-discriminators
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Abstract (arXiv)
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.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Jan 2024.
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Citing papers per year: 2024: 1; 2025: 3.
4 papers.
- 2025LLaSE-G1: Incentivizing Generalization Capability for LLaMA-based Speech Enhancementcited by 19
- 2024Is Self-Supervised Learning Enough to Fill in the Gap? A Study on Speech Inpaintingcited by 2
- 2025TS-URGENet: A Three-stage Universal Robust and Generalizable Speech Enhancement Networkcited by 2
- 2025High-Fidelity Speech Enhancement via Discrete Audio Tokenscited by 2
- 2025High-Fidelity Speech Enhancement via Discrete Audio Tokens2 Oct 2025
- 2025TS-URGENet: A Three-stage Universal Robust and Generalizable Speech Enhancement Network24 May 2025
- 2025LLaSE-G1: Incentivizing Generalization Capability for LLaMA-based Speech Enhancement1 Mar 2025
- 2024Is Self-Supervised Learning Enough to Fill in the Gap? A Study on Speech Inpainting30 May 2024