Development and Research of Computer-Aided English-Chinese Translation System Based on Particle Swarm Optimization Programming

This study combines particle swarm optimization programming and computer-aided translation to model English-Chinese translation and designs a computer-aided English-Chinese translation system with a particle swarm optimization algorithm as a collaborative evolutionary strategy. The system is refined into a user environment model, userspace adjustment, network optimization judgment scheme, multi-intelligent body position adjustment scheme, and particle swarm optimization algorithm; the fitness function, particle structure, population structure, and particle update strategy particle swarm algorithm are designed. In this study, we propose to improve the system of the Seq2seq model and offer the conversion layer. In the existing Seq2seq model, the source language sequence generates a representation vector through the encoder. Then the representation vector is directly used as the initial state of the decoder to generate the target language sequence. The application of computer-aided translation software to study abroad text translation is a brand-new attempt worth exploring. To improve translation speed and efficiency of study abroad texts, this study explores the practical process of using CAT software-assisted text translation, summarizes the translation practice, and puts forward relevant suggestions by analyzing the operation steps and problems that arise in the three stages of retranslation, translation, and posttranslation. It is found that computer-aided software is applicable to improve the translation efficiency of texts to a certain extent.