2 citations · 2 across the 10 of their papers we have counts for
12 papers
Representation-Regularized Convolutional Audio Transformer for Audio Understanding
Bing Han, Chushu Zhou, Yifan Yang +4
Bootstrap-based Self-Supervised Learning (SSL) has achieved remarkable progress in audio understanding. However, existing methods typically operate at a single level of granularity…
SLM-SS: Speech Language Model for Generative Speech Separation
Tianhua Li, Chenda Li, Wei Wang +4
Speech separation (SS) has advanced significantly with neural network-based methods, showing improved performance on signal-level metrics. However, these methods often struggle to…
UrgentMOS: Unified Multi-Metric and Preference Learning for Robust Speech Quality Assessment
Wei Wang, Wangyou Zhang, Chenda Li +12
Automatic speech quality assessment has become increasingly important as modern speech generation systems continue to advance, while human listening tests remain costly, time-consu…
ICASSP 2026 URGENT Speech Enhancement Challenge
Chenda Li, Wei Wang, Marvin Sach +8
The ICASSP 2026 URGENT Challenge advances the series by focusing on universal speech enhancement (SE) systems that handle diverse distortions, domains, and input conditions. This o…
Lightweight Front-end Enhancement for Robust ASR via Frame Resampling and Sub-Band Pruning
Siyi Zhao, Wei Wang, Yanmin Qian
Recent advancements in automatic speech recognition (ASR) have achieved notable progress, whereas robustness in noisy environments remains challenging. While speech enhancement (SE…
MeanSE: Efficient Generative Speech Enhancement with Mean Flows
Jiahe Wang, Hongyu Wang, Wei Wang +5
Speech enhancement (SE) improves degraded speech's quality, with generative models like flow matching gaining attention for their outstanding perceptual quality. However, the flow-…