most citedAMFFCN: Attentional Multi-layer Feature Fusion Convolution Network for Audio-visual Speech Enhancement

2 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

eess.AS2022

GLD-Net: Improving Monaural Speech Enhancement by Learning Global and Local Dependency Features with GLD Block

Xinmeng Xu, Yang Wang, Jie Jia +2

For monaural speech enhancement, contextual information is important for accurate speech estimation. However, commonly used convolution neural networks (CNNs) are weak in capturing…

eess.AS2021★ 2 cited

AMFFCN: Attentional Multi-layer Feature Fusion Convolution Network for Audio-visual Speech Enhancement

Xinmeng Xu, Jianjun Hao

Audio-visual speech enhancement system is regarded to be one of promising solutions for isolating and enhancing speech of desired speaker. Conventional methods focus on predicting…

eess.AS2021

Multi-layer Feature Fusion Convolution Network for Audio-visual Speech Enhancement

Xinmeng Xu, Jianjun Hao

Speech enhancement can potentially benefit from the visual information from the target speaker, such as lip movement and facial expressions, because the visual aspect of speech is…