activity
20192022
most citedCTAL: Pre-training Cross-modal Transformer for Audio-and-Language Representations

5 citations · 7 across the 7 of their papers we have counts for

collaborators

8 papers

cs.SD20215 cited

CTAL: Pre-training Cross-modal Transformer for Audio-and-Language Representations

Hang Li, Yu Kang, Tianqiao Liu +2

Existing audio-language task-specific predictive approaches focus on building complicated late-fusion mechanisms. However, these models are facing challenges of overfitting with li…

cs.SD2021

A Multimodal Machine Learning Framework for Teacher Vocal Delivery Evaluation

Hang Li, Yu Kang, Yang Hao +3

The quality of vocal delivery is one of the key indicators for evaluating teacher enthusiasm, which has been widely accepted to be connected to the overall course qualities. Howeve…

cs.AI20211 cited

An Educational System for Personalized Teacher Recommendation in K-12 Online Classrooms

Jiahao Chen, Hang Li, Wenbiao Ding +1

In this paper, we propose a simple yet effective solution to build practical teacher recommender systems for online one-on-one classes. Our system consists of (1) a pseudo matching…

cs.CL2021

Multi-Task Learning based Online Dialogic Instruction Detection with Pre-trained Language Models

Yang Hao, Hang Li, Wenbiao Ding +4

In this work, we study computational approaches to detect online dialogic instructions, which are widely used to help students understand learning materials, and build effective st…

eess.AS2020

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…

cs.CY2020

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-…