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ترجمة آلة Manipuri-English باستخدام Corpus
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أصبح نموذج الترجمة الآلي غير المقترح (MT)، الذي لديه القدرة على أداء MT دون جمل متوازية باستخدام كورسا مماثلة، نهجا واعدا لتطوير MT بلغات الموارد المنخفضة.ومع ذلك، فإن غالبية الدراسات في MT غير المنشأة قد نظرت في أزواج لغوية غنية بالموارد ذات خصائص لغوية مماثلة.في هذه الورقة، نحقق في فعالية نماذج MT غير الخاضعة للكشف عن كائن قابلة للمقارنة من مانيبوري.Manipuri هي لغة موارد منخفضة لها خصائص لغوية مختلفة من اللغة الإنجليزية.تركز هذه الورقة على تحديد التحديات في بناء نماذج MT غير المقدمة على الكائنات القابلة للمقارنة.من الملاحظات التجريبية المختلفة، من الواضح أن تطوير MT على Corpus المقارنة باستخدام الأساليب غير المعروضة غير ممكن.علاوة على ذلك، تحدد الورقة أيضا الاتجاهات المستقبلية لتطوير MT فعالة لزوج لغة مانيبوري والإنجليزية في ظل سيناريوهات غير مخالفة.
Unsupervised Machine Translation (MT) model, which has the ability to perform MT without parallel sentences using comparable corpora, is becoming a promising approach for developing MT in low-resource languages. However, majority of the studies in unsupervised MT have considered resource-rich language pairs with similar linguistic characteristics. In this paper, we investigate the effectiveness of unsupervised MT models over a Manipuri-English comparable corpus. Manipuri is a low-resource language having different linguistic characteristics from that of English. This paper focuses on identifying challenges in building unsupervised MT models over the comparable corpus. From various experimental observations, it is evident that the development of MT over comparable corpus using unsupervised methods is feasible. Further, the paper also identifies future directions of developing effective MT for Manipuri-English language pair under unsupervised scenarios.
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