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Register a new userHybrid Statistical Machine Translation for English-Myanmar: UTYCC Submission to WAT-2021
الهجين الإحصائي الترجمة للغة الإنجليزية ميانمار: uTyCC تم تقديمها إلى WAT-2021
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في هذه الورقة، نقوم بصف أن نقوم بتقديم طلباتنا إلى WAT-2021 (Nakazawa et al.، 2021) لمهمة اللغة الإنجليزية إلى ميانمار (بورمي).فريقنا، ID: YCC-MT1 ''، ركز على جلب معرفة حرفية إلى وحدة فك الترميز دون تغيير النموذج.لقد استخرجنا يدويا أزواج الكلمة / عبارة الترجمة من ALT Corpus وتطبيق ميزة علامات XML على وحدة فك ترميز موسى (I.E. -XML-إدخال Exclive، -xml -XML-Input شاملة).نوضح أن تقنية الترجمة الهجينة يمكن أن تتحسن بشكل كبير (حوالي 6 درجات بلو) خط الأساس من ثلاثة SMT '' نموذج تسلسل نموذجي "من العبارات المعروفة القائمة على العبارات المعروفة.علاوة على ذلك، حققت هذه الطريقة الهجينة البسيطة ثاني أعلى النتائج بين أنظمة MT المقدمة لمهمة مشاركة الترجمة الإنجليزي إلى ميسمار WAT2021 وفقا ل Bleu (بابينيني وآخرون، 2002) وعشرات AMFM (Banchs et al.، 2015).
In this paper we describe our submissions to WAT-2021 (Nakazawa et al., 2021) for English-to-Myanmar language (Burmese) task. Our team, ID: YCC-MT1'', focused on bringing transliteration knowledge to the decoder without changing the model. We manually extracted the transliteration word/phrase pairs from the ALT corpus and applying XML markup feature of Moses decoder (i.e. -xml-input exclusive, -xml-input inclusive). We demonstrate that hybrid translation technique can significantly improve (around 6 BLEU scores) the baseline of three well-known Phrase-based SMT'', Operation Sequence Model'' and Hierarchical Phrase-based SMT''. Moreover, this simple hybrid method achieved the second highest results among the submitted MT systems for English-to-Myanmar WAT2021 translation share task according to BLEU (Papineni et al., 2002) and AMFM scores (Banchs et al., 2015).
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