摘要
人工智能驱动的语言模型是对传统机器翻译的更新与升级,基于优化算法和深度学习,能够有效提高翻译的效率,但是人工智能驱动的语言模型应用在医学、航空航天、新能源工程等诸多专业领域当中,仍然存在不足之处,翻译的语义理解、文化适应和审美表达,都与人工专业翻译有一定的差距。基于此,研究指出人工智能驱动的语言模型在专业领域翻译中的适应性困境,基于现有技术的发展方向,从算法优化、自适应学习、跨文化数据库研究和美学感知的角度,提出优化策略,进一步推动人工智能驱动的语言模型的发展。
AI-driven language model is an update and upgrade of traditional machine translation.Based on optimization algorithms and deep learning,it can effectively improve the efficiency of translation.However,AI-driven language model is still inadaptable in many professional fields such as medicine,aerospace,new energy engineering,etc.,including semantic understanding,cultural adaptation and aesthetic expression.There is a certain gap between them and manual professional translation.Based on this,the study points out the a⁃daptability dilemma of AI-driven language models in professional translation.Based on the development direction of existing technologies,optimization strategies are proposed from the perspectives of algorithm optimization,adaptive learning,cross-cultural database research and aesthetic perception to further promote the development of AI-driven language models.
作者
曹小琳
Cao Xiaolin(HuBei University of Automotive Technology,Shiyan,Hubei,442000)
出处
《现代英语》
2024年第19期88-90,共3页
Modern English
基金
2024年度湖北省教育科学规划一般项目“基于大语言模型的大学英语自适应学习系统研究——以人工智能驱动个性化学习路径为例”(项目编号:2024GB012)
2024年度教育部产学合作协同育人项目“智慧翻译学习环境下的译者能力培养与评估研究”(项目编号:2410233202)
关键词
语言模型
专业翻译
翻译美学
language model
professional translation
translation aesthetics
