116 citations · 198 across the 5 of their papers we have counts for
5 papers
Information Fusion in Attention Networks Using Adaptive and Multi-level Factorized Bilinear Pooling for Audio-visual Emotion Recognition
Hengshun Zhou, Jun Du, Yuanyuan Zhang +3
Multimodal emotion recognition is a challenging task in emotion computing as it is quite difficult to extract discriminative features to identify the subtle differences in human em…
Exploring Emotion Features and Fusion Strategies for Audio-Video Emotion Recognition
Hengshun Zhou, Debin Meng, Yuanyuan Zhang +4
The audio-video based emotion recognition aims to classify a given video into basic emotions. In this paper, we describe our approaches in EmotiW 2019, which mainly explores emotio…
Frame-level SpecAugment for Deep Convolutional Neural Networks in Hybrid ASR Systems
Xinwei Li, Yuanyuan Zhang, Xiaodan Zhuang +1
Inspired by SpecAugment -- a data augmentation method for end-to-end ASR systems, we propose a frame-level SpecAugment method (f-SpecAugment) to improve the performance of deep con…
Deep Fusion: An Attention Guided Factorized Bilinear Pooling for Audio-video Emotion Recognition
Yuanyuan Zhang, Zi-Rui Wang, Jun Du
Automatic emotion recognition (AER) is a challenging task due to the abstract concept and multiple expressions of emotion. Although there is no consensus on a definition, human emo…
Attention Based Fully Convolutional Network for Speech Emotion Recognition
Yuanyuan Zhang, Jun Du, Zirui Wang +1
Speech emotion recognition is a challenging task for three main reasons: 1) human emotion is abstract, which means it is hard to distinguish; 2) in general, human emotion can only…