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Register a new userTime-Aware Ancient Chinese Text Translation and Inference
تدرك الوقت الترجمة الصينية القديمة والاستدلال
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في هذه الورقة، نهدف إلى معالجة التحديات المحيطة بترجمة النص الصيني القديم: (1) الفجوة اللغوية بسبب الاختلاف في عصائر النتائج في الترجمات التي هي فقيرة في الجودة، و (2) تفتقد معظم الترجمات المعلومات السياقيةغالبا ما يكون هذا أمرا ضروريا للغاية لفهم النص.تحقيقا لهذه الغاية، نحسن تقنيات الترجمة السابقة عن طريق اقتراح ما يلي: نحن نورد المهمة كهجوم تنبؤ متعدد الملصقات حيث يتنبأ النموذج كل من الترجمة وعصرها الخاص.نلاحظ أن هذا يساعد على سد الفجوة اللغوية كما يتم استخدام السياق الزمني أيضا كمعلومات مساعدة.نحن نقوم بالتحقق من طريقنا على كوربوس موازية مشروح مع معلومات التسلسل الزمني وإظهار فعاليتها تجريبيا في إنتاج مخرجات الترجمة عالية الجودة.نقوم بإصدار كل من التعليمات البرمجية وبيانات البحث في المستقبل.
In this paper, we aim to address the challenges surrounding the translation of ancient Chinese text: (1) The linguistic gap due to the difference in eras results in translations that are poor in quality, and (2) most translations are missing the contextual information that is often very crucial to understanding the text. To this end, we improve upon past translation techniques by proposing the following: We reframe the task as a multi-label prediction task where the model predicts both the translation and its particular era. We observe that this helps to bridge the linguistic gap as chronological context is also used as auxiliary information. We validate our framework on a parallel corpus annotated with chronology information and show experimentally its efficacy in producing quality translation outputs. We release both the code and the data for future research.
References used
https://aclanthology.org/
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