Comparison of Translation Techniques by Google Translate and U-Dictionary: How Differently Does Both Machine Translation Tools Perform in Translating?

K. Sipayung, N. M. Sianturi, I. Made, Dwipa Arta, Yeti Rohayati, Diani Indah
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引用次数: 1

Abstract

Better translation produced by computation linguistics should be evaluated through linguistics theory. This research aims to describe translation techniques between Google Translate and U-Dictionary. The study used a qualitative research method with a descriptive design. This design was used to describe the occurrences of translation techniques in both translation machine, with the researchers serving as an instrument to compare translation techniques which is produced on machine. The data are from expository text entitled “Importance of Good Manners in Every Day Life”. The total data are 122 words/phrases which are pairs of translations, English as source language and Indonesia as target language. The result shows that Google Translate apply five of Molina & Albir’s (2002) eighteen translation techniques, while U-dictionary apply seven techniques. Google Translate dominantly apply literal translation techniques (86,8%) followed by reduction translation techniques (4,9%). U-dictionary also dominantly apply literal translation techniques (75,4%), but follows with the variation translation techniques (13,1%). This study showed that both machines produced different target texts for the same source language due to different applications of techniques, with U-dictionary proven to apply more variety of translation techniques than Google Translate. The researcher hopes this study can be used as an evaluation for improving the performance of machine translations.
Google翻译与U-Dictionary翻译技术的比较:两种机器翻译工具在翻译上有何不同?
计算语言学产生的更好的翻译应该用语言学理论来评价。本研究旨在描述谷歌翻译和U-Dictionary之间的翻译技术。本研究采用描述性设计的定性研究方法。该设计用于描述翻译技术在两种翻译机器中的出现情况,研究人员作为一种工具来比较机器上产生的翻译技术。这些数据来自题为“良好礼仪在日常生活中的重要性”的说明性文章。总数据为122个单词/短语,以英语为源语言,印尼语为目标语言,以翻译对的形式进行。结果表明,Google翻译运用了Molina & alir(2002)的18种翻译技巧中的5种,而U-dictionary运用了7种。谷歌翻译主要采用直译技术(86.8%),其次是还原翻译技术(4.9%)。U-dictionary也以直译为主(75.4%),其次是变异翻译(13.1%)。本研究表明,由于技术应用的不同,两台机器对同一源语言产生了不同的目标文本,U-dictionary被证明比Google翻译应用了更多的翻译技术。研究人员希望这项研究可以作为提高机器翻译性能的一个评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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