20 citations · 60 across the 25 of their papers we have counts for
8 papers · 1 filter
Learning Fine-Grained Cross Modality Excitement for Speech Emotion Recognition
Hang Li, Wenbiao Ding, Zhongqin Wu +1
Speech emotion recognition is a challenging task because the emotion expression is complex, multimodal and fine-grained. In this paper, we propose a novel multimodal deep learning…
Mathematical Word Problem Generation from Commonsense Knowledge Graph and Equations
Tianqiao Liu, Qiang Fang, Wenbiao Ding +3
There is an increasing interest in the use of mathematical word problem (MWP) generation in educational assessment. Different from standard natural question generation, MWP generat…
Representation Learning from Limited Educational Data with Crowdsourced Labels
Wentao Wang, Guowei Xu, Wenbiao Ding +4
Representation learning has been proven to play an important role in the unprecedented success of machine learning models in numerous tasks, such as machine translation, face recog…
Automatic Dialogic Instruction Detection for K-12 Online One-on-one Classes
Shiting Xu, Wenbiao Ding, Zitao Liu
Online one-on-one class is created for highly interactive and immersive learning experience. It demands a large number of qualified online instructors. In this work, we develop six…
Neural Multi-Task Learning for Teacher Question Detection in Online Classrooms
Gale Yan Huang, Jiahao Chen, Haochen Liu +6
Asking questions is one of the most crucial pedagogical techniques used by teachers in class. It not only offers open-ended discussions between teachers and students to exchange id…
Siamese Neural Networks for Class Activity Detection
Hang Li, Zhiwei Wang, Jiliang Tang +2
Classroom activity detection (CAD) aims at accurately recognizing speaker roles (either teacher or student) in classrooms. A CAD solution helps teachers get instant feedback on the…
Identifying At-Risk K-12 Students in Multimodal Online Environments: A Machine Learning Approach
Hang Li, Wenbiao Ding, Zitao Liu
With the rapid emergence of K-12 online learning platforms, a new era of education has been opened up. It is crucial to have a dropout warning framework to preemptively identify K-…
NeuCrowd: Neural Sampling Network for Representation Learning with Crowdsourced Labels
Yang Hao, Wenbiao Ding, Zitao Liu
Representation learning approaches require a massive amount of discriminative training data, which is unavailable in many scenarios, such as healthcare, smart city, education, etc.…