Design and Practice of English Learning Support Systems in Intelligent Housing Environments: Exploring the Integration of Technology and Education

Abstract

In order to enhance the effectiveness of classroom teaching, this paper designs and builds a set of English learning support system by combining an intelligent housing environment based on multimedia technology with English teaching. The system architecture mainly includes four functional layers. The data layer relies on the collaboration of multiple servers to realize the transmission and preservation of data. The algorithm layer adopts deep learning algorithms to complete semantic understanding and classification of utterances. The intermediate logic layer accomplishes speech recognition and intelligent dialog through the AI module, the script module is used to process the business logic in the speech data, and the image module recognizes and simulates residential scenes, characters, actions and expressions. The performance layer is equivalent to the client, supporting operations such as system login, system settings and logging out. The experimental results show that the system takes less than 30s to respond to user requests such as questions, corrections, pre-class pre-study and post-class consolidation, and the accuracy of the system in intent recognition and slot value classification of English semantics is more than 95%. This shows that the system's stable performance and high semantic recognition accuracy in the intelligent housing environment can effectively improve students' English learning efficiency in daily life scenarios.