| Summary: | Nowadays, translation technology based on artificial intelligence (AI) has gradually matured. Traditional translation teaching methods have many limitations, such as time and space limitations, increased labor costs, etc. In this context, this article explored the application of translation technology based on AI in translation teaching. In this paper, neural machine translation (NMT) algorithm was used to encode and decode the original text to generate the corresponding translation. The statistical machine translation (SMT) algorithm was used to build the translation model, which was based on the statistical model. The algorithm searched for the best translation hypothesis through inference, which can improve the accuracy and readability of translation. Compared with traditional machine translation (MT), the accuracy rate of AI based translation in this paper reached 97 %, which was far higher than traditional MT and more suitable for teaching. The improvement in student translation was also relatively obvious, which can be clearly seen through students’ translation test scores. At the same time, the teacher's satisfaction with the AI translation teaching system in this article was also high, with an average score of 92 points. Through the application research of translation technology based on AI in translation teaching, AI translation teaching has a positive promoting effect on improving students’ translation level and efficiency.
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