3 papers
eess.AS2026
Rethinking Flow and Diffusion Bridge Models for Speech Enhancement
Dahan Wang, Jun Gao, Tong Lei +4
Flow matching and diffusion bridge models have emerged as leading paradigms in generative speech enhancement, modeling stochastic processes between paired noisy and clean speech si…
eess.AS2026
UL-UNAS: Ultra-Lightweight U-Nets for Real-Time Speech Enhancement via Network Architecture Search
Xiaobin Rong, Leyan Yang, Dahan Wang +4
Lightweight models are essential for real-time speech enhancement applications. In recent years, there has been a growing trend toward developing increasingly compact models for sp…
eess.AS2025
Adaptive Convolution for CNN-based Speech Enhancement Models
Dahan Wang, Xiaobin Rong, Shiruo Sun +3
Deep learning-based speech enhancement methods have significantly improved speech quality and intelligibility. Convolutional neural networks (CNNs) have been proven to be essential…