基于语料库的人机翻译对比研究——以经济类新闻为例
A Corpus-Based Comparative Study of Human and Machine Translation in Economic News

随着全球经济一体化与人工智能技术的发展，ChatGPT等机器翻译在经济新闻翻译中提效显著，但仍面临专业术语、文化背景及语义差异的挑战。本研究以2023年5月至2024年5月间《中国日报》的双语经济新闻为例，运用语料库手段与案例分析的方法，聚焦于人工翻译与ChatGPT机器翻译在词汇多样性方面的表现，旨在揭示两者在经济新闻翻译中的差异。研究发现，尽管ChatGPT能实现基础性的语言转换，但人工翻译在保持原文语义精准性的同时，展现出更高的词汇多样性和文化适应性，尤其在处理复杂专业术语和特定语境时表现更优。本研究不仅深化了对经济新闻翻译中人工与机器翻译差异的理解，推动人机翻译的协同发展，同时为翻译研究提供新的语料库应用视角。
With the development of global economic integration and artificial intelligence technology, machine translation tools such as ChatGPT have made significant improvements in economic news translation, but it still confronts challenges due to differences in professional terminology, cultural backgrounds and semantics. Taking the bilingual economic news published in China Daily from May 2023 to May 2024 as an example, this study employs corpus-based and case analysis methods to focus on the performance of human translation and ChatGPT machine translation in terms of lexical diversity, aiming to reveal the differences between the two in economic news translation. The study found that although ChatGPT can achieve basic language transformation, human translation shows higher lexical diversity and cultural adaptability while maintaining the semantic accuracy of the original text, especially when dealing with complex professional terms and specific contexts. This study not only deepens the understanding of the differences between human and machine translation in economic news translation, promotes the collaborative development of human-machine translation, and provides a new perspective for corpus application in translation research.