University English Translation Teaching in the Context of Artificial Intelligence: Problems and Countermeasures

With the rapid development of artificial intelligence, university English translation teaching faces many challenges and opportunities. This article studies the problems in teaching in this context and proposes effective countermeasures. Diagnostic analysis and factor analysis are used in the article to conduct an in-depth study of the three levels of the teaching process: knowledge skills, autonomy, and emotional development. The students achieved a 70% mastery rate in knowledge and skills, while their independence and emotional development performance was 60% and 50%, respectively. This paper proposes an English speech translation system based on artificial intelligence to enhance teaching effectiveness. After a 14-week teaching experiment, the average grade of the students in the experimental class improved by about 6.82 points compared to the traditional teaching class, proving the system’s effectiveness. The study diagnosed the current problems in university English translation teaching, verified the potential of AI technology in improving teaching quality through empirical research, and combined with AI technology can effectively improve the quality and efficiency of university English translation teaching.