62 citations · 89 across the 5 of their papers we have counts for
5 papers
Joint Noise Reduction and Listening Enhancement for Full-End Speech Enhancement
Haoyu Li, Yun Liu, Junichi Yamagishi
Speech enhancement (SE) methods mainly focus on recovering clean speech from noisy input. In real-world speech communication, however, noises often exist in not only speaker but al…
The PCG-AIID System for L3DAS22 Challenge: MIMO and MISO convolutional recurrent Network for Multi Channel Speech Enhancement and Speech Recognition
Jingdong Li, Yuanyuan Zhu, Dawei Luo +3
This paper described the PCG-AIID system for L3DAS22 challenge in Task 1: 3D speech enhancement in office reverberant environment. We proposed a two-stage framework to address mult…
Uformer: A Unet based dilated complex & real dual-path conformer network for simultaneous speech enhancement and dereverberation
Yihui Fu, Yun Liu, Jingdong Li +4
Complex spectrum and magnitude are considered as two major features of speech enhancement and dereverberation. Traditional approaches always treat these two features separately, ig…
DCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement
Yanxin Hu, Yun Liu, Shubo Lv +6
Speech enhancement has benefited from the success of deep learning in terms of intelligibility and perceptual quality. Conventional time-frequency (TF) domain methods focus on pred…
Sub-Band Knowledge Distillation Framework for Speech Enhancement
Xiang Hao, Shixue Wen, Xiangdong Su +3
In single-channel speech enhancement, methods based on full-band spectral features have been widely studied. However, only a few methods pay attention to non-full-band spectral fea…