13 papers
CoFi-Lite: Pushing the Limits of Ultra-Lightweight Speech Enhancement
Leyan Yang, Dahan Wang, Xiaobin Rong +2
Ultra-lightweight models are essential for the deployment of deep learning-based speech enhancement algorithms on edge devices. Although recent approaches have achieved a certain b…
StuPASE: Towards Low-Hallucination Studio-Quality Generative Speech Enhancement
Xiaobin Rong, Jun Gao, Zheng Wang +3
Achieving high perceptual quality without hallucination remains a challenge in generative speech enhancement (SE). A representative approach, PASE, is robust to hallucination but h…
PhASE-Flow: Phonetic-Conditioned Acoustic Flow Matching in SSL Representation Domain for Speech Enhancement
Jun Gao, Xiaobin Rong, Yu Sun +2
Flow matching (FM) enables high-fidelity generation, while self-supervised learning (SSL) speech models provide hierarchical representations spanning acoustic and phonetic levels.…
HALO: Half-Frame-Rate Adaptive Learnable Operator for Lightweight STFT-Based Speech Enhancement
Jiadong Zhao, Dahan Wang, Yu Sun +5
STFT-based speech enhancement typically adopts overlapping analysis frames. While overlap is essential for stable STFT processing, it makes adjacent frames highly correlated, causi…
FSC-Net: Integrating Fast Fourier Convolutions and Progressive Learning for Speech Bandwidth Extension
Xinan Chen, Xiaobin Rong, Qinwen Hu +2
Speech bandwidth extension (BWE) aims to reconstruct high-fidelity wideband audio from narrowband inputs. While recent approaches have made significant progress, they often struggl…
Reducing Linguistic Hallucination in LM-Based Speech Enhancement via Noise-Invariant Acoustic-Semantic Distillation
Zheng Wang, Xiaobin Rong, Hang Su +6
Language model (LM)-based speech enhancement (SE) can generate natural-sounding speech, but under severe noise it often suffers from unreliable conditioning, leading to perceptuall…