Speech Emotions Recognition for Online Education

The severe circumstances caused by COVID-19 make online education the best replacement for regular face-to-face education for continuing the education process. One year ago, and till now most schools adopted online learning during this pandemic shutdown, which indicates the applicability of this teaching methodology. However, the efficiency of this method needs to be improved to guarantee its effectiveness. Although face-to-face teaching has many advantages over online education, there is a chance to promote online learning by utilizing the recent techniques of artificial intelligence. From this perspective, we propose a framework to detect and recognize emotions in the speech of students during virtual classes to keep instructors updated with the feelings of students so and can behave accordingly. The approach of detecting emotions from the speech is much more helpful for cases when turning on the cameras at the student's side could be embarrassing. This case is very common, especially for schools in Middle East countries. The proposed framework can also be applied to other similar scenarios such as online meetings.