Design of English teaching system using Artificial Intelligence

Abstract

The process of English teaching is significantly affected by various technological advancements like the Internet of Things Video (IoTV). We start with the analysis of the actual teaching process of English and the direction of student feature recognition. We explore the IoTV reform to use the interpolation method for the student image-based feature recognition algorithm. Accordingly, we discover an intelligent algorithm for student feature recognition to improve the effectiveness of the IoTV. The intelligence algorithm for student feature recognition is designed using the Artificial Intelligence (AI) method. The proposed model combines voice recognition and text-to-speech technology to create functional modules of an English teaching system that change the traditional teaching mode and adjust teaching strategies in real-time based on student status based on feature recognition. Finally, this study demonstrates the practical effect of AI on the IoTV system through student feature recognition and classroom instruction assessment. Experiment outcomes reveal the efficiency of the AI-based IoTV system.