activity
20172021
most citedComplementary Fusion of Multi-Features and Multi-Modalities in Sentiment Analysis

54 citations · 63 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SD2021

An Empirical Study on End-to-End Singing Voice Synthesis with Encoder-Decoder Architectures

Dengfeng Ke, Yuxing Lu, Xudong Liu +3

With the rapid development of neural network architectures and speech processing models, singing voice synthesis with neural networks is becoming the cutting-edge technique of digi…

cs.SD2021

Speech Enhancement using Separable Polling Attention and Global Layer Normalization followed with PReLU

Dengfeng Ke, Jinsong Zhang, Yanlu Xie +2

Single channel speech enhancement is a challenging task in speech community. Recently, various neural networks based methods have been applied to speech enhancement. Among these mo…

cs.CV2020★ 3 cited

Dynamically Mitigating Data Discrepancy with Balanced Focal Loss for Replay Attack Detection

Yongqiang Dou, Haocheng Yang, Maolin Yang +2

It becomes urgent to design effective anti-spoofing algorithms for vulnerable automatic speaker verification systems due to the advancement of high-quality playback devices. Curren…

cs.CL2019★ 54 cited

Complementary Fusion of Multi-Features and Multi-Modalities in Sentiment Analysis

Feiyang Chen, Ziqian Luo, Yanyan Xu +1

Sentiment analysis, mostly based on text, has been rapidly developing in the last decade and has attracted widespread attention in both academia and industry. However, the informat…

cs.LG2017

Trainable back-propagated functional transfer matrices

Cheng-Hao Cai, Yanyan Xu, Dengfeng Ke +2

Connections between nodes of fully connected neural networks are usually represented by weight matrices. In this article, functional transfer matrices are introduced as alternative…

cs.AI2017★ 6 cited

Learning of Human-like Algebraic Reasoning Using Deep Feedforward Neural Networks

Cheng-Hao Cai, Dengfeng Ke, Yanyan Xu +1

There is a wide gap between symbolic reasoning and deep learning. In this research, we explore the possibility of using deep learning to improve symbolic reasoning. Briefly, in a r…