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Register a new userTMU NMT System with Japanese BART for the Patent task of WAT 2021
نظام TMU NMT مع بارت اليابانية لمهمة براءات الاختراع في WAT 2021
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في هذه الورقة، نقدم نظام TMU العصبي الخاص بنا (NMT) مقدم له مهمة براءات الاختراع (اليابانية والإنجليزية الكورية اليابانية) من ورشة العمل الثامنة حول الترجمة الآسيوية (Nakazawa et al.، 2021).في الآونة الأخيرة، اقترحت عدة دراسات طرز فك التشفير المدربة مسبقا باستخدام بيانات أحادية الأونلينغ.تم عرض واحدة من النماذج المدربة مسبقا، بارت (لويس وآخرون، 2020)، لتحسين دقة الترجمة عن طريق ضبط الدقيقة مع بيانات ثنائية اللغة.ومع ذلك، قاموا بتجريد الترجمة الإنجليزية الرومانية فقط باستخدام اللغة الإنجليزية بارت.في هذه الورقة، ندرس فعالية بارت اليابانية باستخدام مكتب براءات الاختراع الياباني Corpus 2.0.تشير تجاربنا إلى أن البارت الياباني يمكنه أيضا تحسين دقة الترجمة في كل من الترجمات اليابانية اليابانية والإنجليزية الكورية.
In this paper, we introduce our TMU Neural Machine Translation (NMT) system submitted for the Patent task (Korean Japanese and English Japanese) of 8th Workshop on Asian Translation (Nakazawa et al., 2021). Recently, several studies proposed pre-trained encoder-decoder models using monolingual data. One of the pre-trained models, BART (Lewis et al., 2020), was shown to improve translation accuracy via fine-tuning with bilingual data. However, they experimented only Romanian!English translation using English BART. In this paper, we examine the effectiveness of Japanese BART using Japan Patent Office Corpus 2.0. Our experiments indicate that Japanese BART can also improve translation accuracy in both Korean Japanese and English Japanese translations.
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