16 citations · 34 across the 9 of their papers we have counts for
7 papers · 1 filter
MeloTrans: A Text to Symbolic Music Generation Model Following Human Composition Habit
Yutian Wang, Wanyin Yang, Zhenrong Dai +3
At present, neural network models show powerful sequence prediction ability and are used in many automatic composition models. In comparison, the way humans compose music is very d…
Optimizing Shoulder to Shoulder: A Coordinated Sub-Band Fusion Model for Real-Time Full-Band Speech Enhancement
Guochen Yu, Andong Li, Wenzhe Liu +3
Due to the high computational complexity to model more frequency bands, it is still intractable to conduct real-time full-band speech enhancement based on deep neural networks. Rec…
DBT-Net: Dual-branch federative magnitude and phase estimation with attention-in-attention transformer for monaural speech enhancement
Guochen Yu, Andong Li, Hui Wang +3
The decoupling-style concept begins to ignite in the speech enhancement area, which decouples the original complex spectrum estimation task into multiple easier sub-tasks i.e., mag…
Dual-branch Attention-In-Attention Transformer for single-channel speech enhancement
Guochen Yu, Andong Li, Chengshi Zheng +3
Curriculum learning begins to thrive in the speech enhancement area, which decouples the original spectrum estimation task into multiple easier sub-tasks to achieve better performa…
A Two-stage Complex Network using Cycle-consistent Generative Adversarial Networks for Speech Enhancement
Guochen Yu, Yutian Wang, Hui Wang +2
Cycle-consistent generative adversarial networks (CycleGAN) have shown their promising performance for speech enhancement (SE), while one intractable shortcoming of these CycleGAN-…
Joint magnitude estimation and phase recovery using Cycle-in-Cycle GAN for non-parallel speech enhancement
Guochen Yu, Andong Li, Yutian Wang +3
For the lack of adequate paired noisy-clean speech corpus in many real scenarios, non-parallel training is a promising task for DNN-based speech enhancement methods. However, becau…
CycleGAN-based Non-parallel Speech Enhancement with an Adaptive Attention-in-attention Mechanism
Guochen Yu, Yutian Wang, Chengshi Zheng +2
Non-parallel training is a difficult but essential task for DNN-based speech enhancement methods, for the lack of adequate noisy and paired clean speech corpus in many real scenari…