Design of Computer Intelligent Translation System Based on Natural Language Processing

With the rapid development of social economy and the increasing frequency of global trade, translation services are crucial to international trade. However, the traditional translation system supports a single language, which cannot meet the translation efficiency and accuracy required by the users. The realization of multilingual mutual translation has become the bottleneck of the development of international trade. The application of computer intelligent translation system in international trade has become a research hotspot. This paper studies the computer intelligent translation system, combines natural language processing, machine translation and neural network technology, and designs a computer intelligent translation system based on natural language processing. The architecture of the whole system includes functional modules, system structure and hardware structure. In this paper, the system is divided into functional modules and uses this model to identify and analyze the results of machine translation. The experimental results show that the computer intelligent translation system designed here has high accuracy without manual intervention. Compared with traditional machine translation methods, this system shows obvious advantages in both translation accuracy and time cost. By combining natural language processing, machine translation and neural network technology, the system can better meet the needs of multilingual mutual translation and improve the accuracy and efficiency of translation. It can effectively improve the accuracy of translation and reduce the time cost while ensuring the quality of translation.