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Register a new userKakao Enterprise's WMT21 Machine Translation Using Terminologies Task Submission
الترجمة الآلية ل Cakao Enterprise Machine باستخدام مصطلحات تقديم المهمة
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تصف هذه الورقة تقديم Kakao Enterprise إلى الترجمة الآلية المشتركة WMT21 باستخدام مهمة المصطلحات.نحن ندمج قيود المصطلحات من خلال التدريب المسبق مع التوضيحات المستهدفة التلقائية والضبط بشكل جيد مع التعليقات التوضيحية المستهدفة الدقيقة باستخدام مجموعة بيانات المصطلحات المحددة.ينتجج هذا النهج نموذجا يحقق نتائج رائعة من حيث جودة الترجمة واتساق الأجل، المرتبة الأولى بناء على المذنب في اتجاه لغة EN → FR.علاوة على ذلك، نستكشف أساليب مختلفة مثل الترجمة الخلفية، ومصطلحات تدريب صريحة كبيانات متوازية إضافية، واختيار بيانات داخل المجال.
This paper describes Kakao Enterprise's submission to the WMT21 shared Machine Translation using Terminologies task. We integrate terminology constraints by pre-training with target lemma annotations and fine-tuning with exact target annotations utilizing the given terminology dataset. This approach yields a model that achieves outstanding results in terms of both translation quality and term consistency, ranking first based on COMET in the En→Fr language direction. Furthermore, we explore various methods such as back-translation, explicitly training terminologies as additional parallel data, and in-domain data selection.
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