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

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.