Using Collaborative Recommendation in English Teaching for Financial Company Employees in the Health Sector

Abstract

This paper examines the actual teaching process of English and begins with a focus on student feature recognition and English classroom reform, using the in-trepidation method to perform a student feature image recognition algorithm, and then improving the algorithm to obtain an intelligent algorithm suitable for student feature recognition. Furthermore, this paper uses multi-media resources to combine voice recognition technology and text-to-speech technology to create functional modules of the 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 article demonstrates the practical effect of the artificial intelligence English teaching system during system testing by recognizing student features and evaluating classroom instruction. The findings of experimental research suggest that an artificial intelligence-based English teaching system has some effect.