E-learning application in english writing classroom based on neural machine translation and semantic analysis algorithms

At present, there are some problems in traditional English writing teaching, such as the lack of practice opportunities and the lack of timely feedback. The aim of this study is to design an e-learning platform to improve students' writing ability through neural machine translation and semantic analysis algorithms. This paper introduces the basic principles of neural machine translation and semantic analysis algorithms and their applications in translation and semantic understanding. In this paper, a computer English writing correction model based on neural machine translation and semantic analysis algorithm is proposed and applied to e-learning platform. The platform structure is constructed. The neural machine translation model is used to translate and transform the original writing content into standard English expressions. Then, semantic analysis algorithm is used to detect errors and propose suggestions for modification. The results show that the e-learning platform can provide personalized and timely feedback, and students' writing ability has been significantly improved on the elearning platform. They have improved their writing skills and presentation through exercises and submissions through the e-learning platform.