Zhao Tao, Alias Mazni Binti
Faculty of Management, Multimedia University, Cyberjaya, Malaysia.
School of International Education, Henan University of Engineering, Zhengzhou, Henan, China.
PeerJ Comput Sci. 2024 Nov 12;10:e2396. doi: 10.7717/peerj-cs.2396. eCollection 2024.
With the continued development of information technology and increased global cultural exchanges, translation has gained significant attention. Traditional manual translation relies heavily on dictionaries or personal experience, translating word by word. While this method ensures high translation quality, it is often too slow to meet the demands of today's fast-paced environment. Computer-assisted translation (CAT) addresses the issue of slow translation speed; however, the quality of CAT translations still requires rigorous evaluation. This study aims to answer the following questions: How do CAT systems that use automated programming fare compared to more conventional methods of human translation when translating English vocabulary? (2) How can CAT systems be improved to handle difficult English words, specialised terminology, and semantic subtleties? The working premise is that CAT systems that use automated programming techniques will outperform traditional methods in terms of translation accuracy. English vocabulary plays a crucial role in translation, as words can have different meanings depending on the context. CAT systems improve their translation accuracy by utilising specific automated programs and building a translation through translation memory technology. This study compares the accuracy of English vocabulary translations produced by CAT based on automatic programming with those produced by traditional manual translation. Experimental results demonstrate that CAT based on automatic programming is 8% more accurate than traditional manual translation when dealing with complex English vocabulary sentences, professional jargon, English acronyms, and semantic nuances. Consequently, compared to conventional human translation, CAT can enhance the accuracy of English vocabulary translation, making it a valuable tool in the translation industry.
随着信息技术的不断发展以及全球文化交流的增加，翻译受到了广泛关注。传统的人工翻译严重依赖词典或个人经验，逐字翻译。虽然这种方法能确保较高的翻译质量，但往往速度过慢，无法满足当今快节奏环境的需求。计算机辅助翻译（CAT）解决了翻译速度慢的问题；然而，CAT翻译的质量仍需严格评估。本研究旨在回答以下问题：（1）在翻译英语词汇时，使用自动编程的CAT系统与更传统的人工翻译方法相比如何？（2）如何改进CAT系统以处理难词、专业术语和语义细微差别？研究的工作前提是，使用自动编程技术的CAT系统在翻译准确性方面将优于传统方法。英语词汇在翻译中起着至关重要的作用，因为单词的含义会因上下文而异。CAT系统通过使用特定的自动程序并借助翻译记忆技术建立翻译库来提高其翻译准确性。本研究比较了基于自动编程的CAT所产生的英语词汇翻译与传统人工翻译的准确性。实验结果表明，在处理复杂的英语词汇句子、专业术语、英语首字母缩略词和语义细微差别时，基于自动编程的CAT比传统人工翻译的准确性高8%。因此，与传统的人工翻译相比，CAT可以提高英语词汇翻译的准确性，使其成为翻译行业中的一个有价值的工具。
