6 citations · 13 across the 6 of their papers we have counts for
6 papers
Improving Visual Speech Enhancement Network by Learning Audio-visual Affinity with Multi-head Attention
Xinmeng Xu, Yang Wang, Jie Jia +2
Audio-visual speech enhancement system is regarded as one of promising solutions for isolating and enhancing speech of desired speaker. Typical methods focus on predicting clean sp…
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…
VSEGAN: Visual Speech Enhancement Generative Adversarial Network
Xinmeng Xu, Yang Wang, Dongxiang Xu +4
Speech enhancement is an essential task of improving speech quality in noise scenario. Several state-of-the-art approaches have introduced visual information for speech enhancement…
Generative Model for Heterogeneous Inference
Honggang Zhou, Yunchun Li, Hailong Yang +2
Generative models (GMs) such as Generative Adversary Network (GAN) and Variational Auto-Encoder (VAE) have thrived these years and achieved high quality results in generating new s…
Using Deep Neural Network Approximate Bayesian Network
Jie Jia, Honggang Zhou, Yunchun Li
We present a new method to approximate posterior probabilities of Bayesian Network using Deep Neural Network. Experiment results on several public Bayesian Network datasets shows t…
BigRoots: An Effective Approach for Root-cause Analysis of Stragglers in Big Data System
Honggang Zhou, Yunchun Li, Hailong Yang +2
Stragglers are commonly believed to have a great impact on the performance of big data system. However, the reason to cause straggler is complicated. Previous works mostly focus on…