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Correleration Analysis Between Teacher's Voice and Students' Facial Expressions for Online and Offline Teaching Feedback

Correleration Analysis Between Teacher's Voice and Students' Facial Expressions for Online and Offline Teaching Feedback

Project Leader: Pascal FUNG
School: School of Engineering
Department: Electronic and Computer Engineering (ECE)
Project Start Year: 2021/22
Description:

Our goal in this project is to maximize the student’s attention/interest in class and help teachers to improve their teaching abilities, in particular but not limited to online teaching. Our idea is that facial/visual reaction can indicate the attentiveness and attention of students. If they are more engaged with the lecture/lecturer, they are more likely to look at the screen or the lecturer. Therefore, this project intends to detect these facial/visual reactions and model the correlation between the student’s facial expressions and the teachers’ vocal signal so as to help teachers improve their teaching ability and create better engagement for students.

Status: Completed
Type of Innovation: Artificial Intelligence
Triennium:
2019-2022
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Department
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