An Automatic Evaluation for Online Machine Translation: Holy Quran Case Study
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 6
Abstract
The number of Free Online Machine Translation (FOMT) users witnessed a spectacular growth since 1994. FOMT systems change the aspects of machine translation (MT) and the mass translated materials using a wide range of natural languages and machine translation systems. Hundreds of millions of people use these FOMT systems to translate the holy Quran (Al-Qur?an) verses from the Arabic language to other natural languages, and vice versa. In this study, an automatic evaluation for the use of FOMT systems to translate Arabic Quranic text into English is conducted. The two well-known FOMT systems (Google and Bing Translators) are chosen to be evaluated in this study using a metric called Assessment of Text Essential Characteristics (ATEC). ATEC metric is one of the automatic evaluation metrics for machine translation systems. ATEC scores the correlation between the output of a machine translation system and professional human reference translation based on word choice, word orders and the similarity between MT output and the human reference translation. Extensive evaluation has been conducted on two well-known FOMT systems to translate Arabic Quranic text into English. This evaluation shows that Google translator performs better than Bing translator in translating Quranic text. It is noticed that the average ATEC score does not exceed 41% which indicates that FOMT systems are ineffective in translating Quranic texts accurately
Authors and Affiliations
Emad AlSukhni, Mohammed Al-Kabi, Izzat Alsmadi
Keywords
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- EP ID EP107084
- DOI 10.14569/IJACSA.2016.070614
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