摘要
近年来,人工智能与机器翻译技术迅猛发展,机器翻译在语言服务行业的应用率呈连续较大幅度增长。虽然机器翻译已取得巨大进步,但是其输出的译文质量仍然无法与职业译者的人工译文相媲美。为发挥两者优势,实现译文质量与翻译效率间的平衡,译后编辑越来越为语言服务行业所采用。此次实践选取的翻译材料为Growing Hope,摘自The Book of Hope: A Survival Guide for Trying Times,是一篇文学类文本。文章通过讲述幸存之树涅槃重生,重换生机。以此来启迪人们,即使是在艰难时刻,也要保持乐观,怀揣希望。本次翻译采用了“机器翻译 + 译后编辑”的模式。选用的机器翻译系统是DeepL翻译,译后编辑以人工编辑 + 课堂讨论为主。根据DeepL机器翻译的质量探讨DeepL在处理文学类文本时存在的问题:词义错译、语句次序错误、语义不连贯等等,并提出对应的译后编辑方法。
In recent years, artificial intelligence and the technology of machine translation have been rapidly developed. Machine translation has been used in a more popular way in the language service in-dustry. Although great progress has been made in machine translation, the quality of its output still cannot be comparable to that of professional translators. In order to give full play to their ad-vantages and achieve a balance between the quality and the efficiency of translation, post-editing has been greatly adopted in the language service industry. The material selected is Growing Hope, which is from the Book of Hope: A Survival Guide for Trying Times and is a literary text. The material is about the survivor tree, which brings back from the dead and put out new leaves herself, in order to inspire people to be optimistic and hopeful, even in difficult times. This translation adopts the mode of “MT + PE”. The selected machine translation system is DeepL, and the PE is mainly based on manual editing and classroom discussion. According to the quality of DeepL, this paper discusses the existing problems of DeepL in handling literary texts, such as misinterpretation of word mean-ings, misordering of sentences, semantic incoherence and so on, and proposes corresponding PE ed-iting methods.
出处
《现代语言学》
2023年第11期5096-5106,共11页
Modern Linguistics
