Design of Oral English Training System Based on Big Data Content Recommendation Algorithm

Abstract

Collaborative filtering is the most widely used and successful recommendation technology in recommendation systems. In view of the problem that the effect of collaborative filtering technology depends on an accurate similarity measurement method and its poor scalability can not deal with big data, in the information age of computer development, all undertakings are developing rapidly. English has long been an important tool for people to communicate with each other, but due to the limitation of learning mode and environment, the level of Chinese oral English is generally low. The cloud computation-based oral English learning system is designed. Users can learn oral English knowledge, simulate oral English testing and establish exclusive dictionaries through mobile terminals. According to the specific learning situation of Chinese English learners, a flexible and expandable virtual interactive platform is constructed through virtual technology and artificial intelligence, and multi-dimensional virtual scenes and intelligent AI roles are designed to realize the communication and learning of AI roles in different scenarios and improve learners' oral ability and language sense knowledge. However, compared with the traditional self-help learning method, there are huge changes. Our modern English self-help learning has basically got rid of the limitation of paper books, and most of it is carried out through the computer network.