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Register a new userTermMind: Alibaba's WMT21 Machine Translation Using Terminologies Task Submission
TermMind: الترجمة الآلية ل ALIBABA من WMT21 باستخدام مصطلحات تقديم المهمة
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تصف هذه الورقة عملنا في الترجمة الآلية لعام 2021 باستخدام المهمة المشتركة للمصطلحات.نشارك في مهمة مصطلحات الترجمة المشتركة في اللغة الإنجليزية إلى زوج اللغة الصينية.لإرضاء قيود المصطلحات على الترجمة، نستخدم استراتيجية تكبير بيانات المصطلحات بناء على نموذج المحول.استخدمنا علامات لوضع علامة وإضافة ترجمة المصطلح إلى الجمل المتطابقة.أنشأنا مصطلحات صناعية باستخدام عبارات تم استخراجها من Corpus ثنائية اللغة لزيادة نسبة ترجمات المصطلح في بيانات التدريب.يتم استخدام المعالجة المفصلة المسبقة والتصفية على البيانات، يتم استخدام أسلوب Finetuning في المجال والكفر في نظامنا.تقدمنا يحصل على نتائج تنافسية في التقييم المستهدف للمصطلحات.
This paper describes our work in the WMT 2021 Machine Translation using Terminologies Shared Task. We participate in the shared translation terminologies task in English to Chinese language pair. To satisfy terminology constraints on translation, we use a terminology data augmentation strategy based on Transformer model. We used tags to mark and add the term translations into the matched sentences. We created synthetic terms using phrase tables extracted from bilingual corpus to increase the proportion of term translations in training data. Detailed pre-processing and filtering on data, in-domain finetuning and ensemble method are used in our system. Our submission obtains competitive results in the terminology-targeted evaluation.
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