Design and implementation of an intelligent teaching system for cabin service training driven by artificial intelligence: a multimodal real-time feedback framework

Abstract

This paper designs an intelligent education system for "Cabin Service" using artificial intelligence algorithms, which is equipped with multimodal perception technology, functional integration and real-time feedback mechanism. The modeling and automatic feedback of speech, images and actions are carried out through FM-DNN. By applying boundary processing and dynamic threshold regulation, the accurate identification and dynamic adjustment of teaching situations are achieved. Experiments have proved that the response rate, data consistency and feedback accuracy of this system are extremely excellent, and it has high stability and engineering scalability, and is suitable for intelligent teaching applications in various environments.