Data generalization processing and fusion machine translation system based on virtual reality technology

Abstract

In the development of digital technology, machine language is one of the important branches. We need to establish a set of perfect, efficient and applicable data generalization processing and fusion methods applicable to practical application scenarios to improve the efficiency of model information transmission. The data processing part in this system mainly includes the model analysis, modeling and simulation. In machine translation, the model should first be transformed into a generalization ability feature function with certain significance. In order to make English translation more accurate and interesting, we can use virtual reality technology to design English translation learning methods and translation software. This paper mainly uses the methods of quantitative analysis and data comparison to make statistics and comparison on the response and transmission quantity of the system in different applications, and obtain the relevant performance of the system. The experimental data shows that the number of data transmission based on RDF is always more than 5 than that of SWIFT.