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Register a new userZero-pronoun Data Augmentation for Japanese-to-English Translation
Zero-proroun - تكبير البيانات للترجمة اليابانية إلى الإنجليزية
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بالنسبة للترجمة اليابانية إلى الإنجليزية، تشكل الضمائر الصفرية في اليابانية تحديا، نظرا لأن النموذج يحتاج إلى استنتاج النموذج وإنتاج الضمير المقابل في الجانب المستهدف من الجملة الإنجليزية.ومع ذلك، على الرغم من أن حل الضمائر الصفرية بالكامل غالبا ما تحتاج إلى سياق خطاب، في بعض الحالات، فإن السياق المحلي في غضون جملة يمنح أدلة على استنتاج الضمير الصفر.في هذه الدراسة، نقترح طريقة تكبير البيانات التي توفر إشارات تدريبية إضافية لنموذج الترجمة لتعلم الارتباطات بين السياق المحلي وضمائر الصفر.نظهر أن الطريقة المقترحة تعمل بشكل كبير على تحسين دقة ترجمة صفر الضمير مع تجارب ترجمة الجهاز في مجال المحادثة.
For Japanese-to-English translation, zero pronouns in Japanese pose a challenge, since the model needs to infer and produce the corresponding pronoun in the target side of the English sentence. However, although fully resolving zero pronouns often needs discourse context, in some cases, the local context within a sentence gives clues to the inference of the zero pronoun. In this study, we propose a data augmentation method that provides additional training signals for the translation model to learn correlations between local context and zero pronouns. We show that the proposed method significantly improves the accuracy of zero pronoun translation with machine translation experiments in the conversational domain.
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