Flow-PLC: Towards Efficient Packet Loss Concealment With Flow Matching

Recent advancements in packet loss concealment (PLC) have introduced diffusion-based generative models that offer high-quality audio reconstruction. However, their high computational costs make them impractical for real-time applications. In this letter, we present Flow-PLC, an efficient PLC model based on the flow-matching framework, designed to address these computational challenges. Flow-PLC achieves a remarkable 23× reduction in inference time compared to diffusion-based PLC models, requiring only five sampling steps to achieve near-optimal reconstruction. By significantly reducing computational complexity while maintaining high-quality results, Flow-PLC represents a substantial advancement in the development of efficient and practical generative PLC systems.

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Publication Details

Journal
IEEE Signal Processing Letters
Published
2025-01-01
DOI
https://doi.org/10.1109/lsp.2025.3553421
Citations
5
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
7.44
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article

Flow-PLC: Towards Efficient Packet Loss Concealment With Flow Matching

Joon‐Hyuk Chang, Da-Hee Yang
5 citations
IEEE Signal Processing Letters
Software-Defined Networks and 5G
7.44
article

Flow-PLC: Towards Efficient Packet Loss Concealment With Flow Matching

Joon‐Hyuk Chang, Da-Hee Yang
article en
5 citations

Abstract

Recent advancements in packet loss concealment (PLC) have introduced diffusion-based generative models that offer high-quality audio reconstruction. However, their high computational costs make them impractical for real-time applications. In this letter, we present Flow-PLC, an efficient PLC model based on the flow-matching framework, designed to address these computational challenges. Flow-PLC achieves a remarkable 23× reduction in inference time compared to diffusion-based PLC models, requiring only five sampling steps to achieve near-optimal reconstruction. By significantly reducing computational complexity while maintaining high-quality results, Flow-PLC represents a substantial advancement in the development of efficient and practical generative PLC systems.

IEEE Signal Processing LettersVol. 32
Hanyang University (KR)
Openalex Percentile: Top 3%
Software-Defined Networks and 5G
7.44
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