Preliminary Study: Speech Emotion Recognition in Online Teaching From the Perspective of Educators Especially Late Deafened

An effective Human Computer Interaction (HCI) for recognizing human emotions automatically is known to as affective computing. Affective computing is achieved through programming, which is meant to detect emotions from facial expressions or verbal utterances. These detected emotions can be further used in many applications. Speech emotion recognition (SER) is one such affective computing application where the detected emotions can be used effectively, particularly in online education. Such an application would allow for the teaching strategies to be tailored for the students, on the basis of their understanding of the ongoing class, which is reflected in their verbal feedback. This valuable application of technology will enhance and support education for all, especially the educators who have issues with hearing verbal feedback from students. The main objective of this study is to find out from educators (with and without hearing impairment) on the necessity of knowing student emotions to enhance teaching outcomes for effective teaching and also the benefits of having an automatic detection system which would display student emotions in an online classroom setting. The outcome of this research clearly indicated how a preliminary user requirement study highlights the need and benefits of implementing a SER system.