24 citations · 24 across the 5 of their papers we have counts for
5 papers
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…
FNSE-SBGAN: Far-field Speech Enhancement with Schrodinger Bridge and Generative Adversarial Networks
Tong Lei, Qinwen Hu, Ziyao Lin +5
The prevailing method for neural speech enhancement predominantly utilizes fully-supervised deep learning with simulated pairs of far-field noisy-reverberant speech and clean speec…
SNR-Progressive Model with Harmonic Compensation for Low-SNR Speech Enhancement
Zhongshu Hou, Tong Lei, Qinwen Hu +3
Despite significant progress made in the last decade, deep neural network (DNN) based speech enhancement (SE) still faces the challenge of notable degradation in the quality of rec…
Harmonic enhancement using learnable comb filter for light-weight full-band speech enhancement model
Xiaohuai Le, Tong Lei, Li Chen +9
With fewer feature dimensions, filter banks are often used in light-weight full-band speech enhancement models. In order to further enhance the coarse speech in the sub-band domain…
Inference skipping for more efficient real-time speech enhancement with parallel RNNs
Xiaohuai Le, Tong Lei, Kai Chen +1
Deep neural network (DNN) based speech enhancement models have attracted extensive attention due to their promising performance. However, it is difficult to deploy a powerful DNN i…