في هذه الورقة، نصف تقاريرنا للمهمة المشتركة ل Loresmt مؤتمر قمة MT 2021.بنينا أنظمة ترجمة إحصائية في كل اتجاه للإنجليزية ⇐⇒ زوج لغة الماراثي.تحدد هذه الورقة تجارب خط الأساس الأولية مع مخططات التزخم المختلفة لتدريب النماذج.باستخدام مخطط التزامن الأمثل، نقوم بإنشاء بيانات اصطناعية ومزيد من البيانات المعززة لمجموعة البيانات لإنشاء المزيد من النماذج الإحصائية.أيضا، نقوم بإعادة ترتيب اللغة الإنجليزية لتتناسب مع بناء جملة الماراثي لتعزيز مجموعة أخرى من النماذج الأساسية والبيانات باستخدام مخططات التكامل المختلفة.نبلغ عن تكوين الأنظمة والنتائج المقدمة التي تنتجها.
In this paper, we describe our submissions for LoResMT Shared Task @MT Summit 2021 Conference. We built statistical translation systems in each direction for English ⇐⇒ Marathi language pair. This paper outlines initial baseline experiments with various tokenization schemes to train models. Using optimal tokenization scheme we create synthetic data and further train augmented dataset to create more statistical models. Also, we reorder English to match Marathi syntax to further train another set of baseline and data augmented models using various tokenization schemes. We report configuration of the submitted systems and results produced by them.
References used
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