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SB-RF: Schr'odinger Bridge Rectified Flow for One-Step Robust Speech Enhancement

2026-06-04 01:50:12
Caixia Lu, Xueyang Lv, Penglong Hu, Jiaming Xu
arXiv_SD
           
Abstract

Generative models have shown impressive results in speech enhancement but often suffer from multi-step inference. We propose SB-RF, a one-step generative framework integrating Rectified Flow (RF) with Schrödinger Bridge (SB) theory. SB-RF constructs a conditional bridge between clean and noisy speech distributions via entropy-regularized optimal transport. By aligning SB trajectories with the optimal transport geodesic through the velocity-matching objective of RF, SB-RF enables high-quality enhancement with one-step generation. Experiments demonstrate that SB-RF achieves leading performance among generative methods on the VoiceBank-DEMAND benchmark. Furthermore, to fully assess performance in challenging real-world scenarios, we evaluate SB-RF on a simulated low signal-to-noise ratio test set using an expanded training dataset. Under these conditions, SB-RF exhibits strong and competitive robustness with high efficiency, validating its potential for real-world applications.

Abstract (translated)

URL

https://arxiv.org/abs/2606.05575

PDF

https://arxiv.org/pdf/2606.05575.pdf

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