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A Comparative Study of English-Persian Translation of Neural Google Translation | ||
| Iranian Journal of Applied Language Studies | ||
| مقاله 17، دوره 9، Proceedings of the First International Conference on Language Focus، دی 2017، صفحه 279-286 اصل مقاله (98.35 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22111/ijals.2017.4233 | ||
| نویسندگان | ||
| Mina Zand Rahimi؛ Moein Madayenzadeh؛ Mahdi Alizadeh | ||
| Shahid Bahonar University of Kerman | ||
| چکیده | ||
| Many studies abroad have focused on neural machine translation and almost all concluded that this method was much closer to humanistic translation than machine translation. Therefore, this paper aimed at investigating whether neural machine translation was more acceptable in English-Persian translation in comparison with machine translation. Hence, two types of text were chosen to be translated by Google Translate. The inputs have been translated in two distinctive methods. The outputs were investigated by the descriptive-comparative human analysis model of Keshavarz. Consequently, the results revealed that approximately the same errors were found in both methods. However, semantic aspects were improved. | ||
| کلیدواژهها | ||
| Neural Google Translation؛ Machine Translation؛ English-Persian Translation؛ Phrase-Based Machine Translation | ||
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آمار تعداد مشاهده مقاله: 1,219 تعداد دریافت فایل اصل مقاله: 563 |
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