Research on Intelligent Translation System Based on Artificial Intelligence Algorithm

Aiming at the practical needs and challenges of bilingual translation, this paper discusses how to apply artificial intelligence algorithm to online translation in order to build an efficient and accurate intelligent translation system. Taking Chinese-French translation as an example, this study first analyzes the current problems in the field of Chinese-French translation, such as semantic information loss caused by cultural differences and translation deviation caused by sentence structure complexity, and clearly points out the great potential of artificial intelligence technology in solving these problems. On this basis, the application principles and implementation strategies of commonly used artificial intelligence algorithms in intelligent translation systems are introduced in detail. By integrating these advanced technologies, a Chinese-French intelligent translation system with self-learning and optimization capabilities is designed and developed. This system can not only accurately translate words and phrases, but also understand and process complex syntactic structures to a certain extent, and effectively retain the cultural connotation and contextual information of the original text. The empirical study shows that with the aid of artificial intelligence algorithm, the intelligent translation system developed by us has significantly improved the translation quality and stability in the Sino-French mutual translation task. This provides an important theoretical basis and technical support for further optimization and improvement of intelligent translation technology, especially for cross-language communication between China and France.