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Register a new userChinese Character Decomposition for Neural MT with Multi-Word Expressions
التحلل الطابع الصيني ل MT العصبي مع تعبيرات متعددة الكلمات
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تم استخدام تحلل الطابع الصيني كميزة لتعزيز نماذج الترجمة الآلية (MT)، والجمع بين المتطرفين في طرازات حرف مستوى الكلمة.حققت العمل الحديث في الأيديوجراف أو تضمين مستوى السكتة الدماغية.ومع ذلك، تبقى الأسئلة حول مستويات التحلل المختلفة من تمثيلات الأحرف الصينية، والراديكالية والسكتات الدماغية، والأمن الأكون مناسبة لجبل.للتحقيق في تأثير تضمين التحلل الصيني بالتفصيل، أي المستويات الجذعية والسكتة الدماغية والسكتة الدماغية، ومدى جودة تحلل هذه التحلل معنى تسلسل الأحرف الأصلية، نقوم بإجراء تحليل مع كل من التقييم الآلي والإنساني ل MT.علاوة على ذلك، يمكننا التحقيق في ما إذا كان يمكن أن يعزز مزيج التعبيرات المتعددة الكلمة المتحللة (MWES) التعلم النموذجي.شهدت تكامل MWE في MT أكثر من عقد من الاستكشاف.ومع ذلك، لم يتم استكشاف mwes المتحللة سابقا.
Chinese character decomposition has been used as a feature to enhance Machine Translation (MT) models, combining radicals into character and word level models. Recent work has investigated ideograph or stroke level embedding. However, questions remain about different decomposition levels of Chinese character representations, radical and strokes, best suited for MT. To investigate the impact of Chinese decomposition embedding in detail, i.e., radical, stroke, and intermediate levels, and how well these decompositions represent the meaning of the original character sequences, we carry out analysis with both automated and human evaluation of MT. Furthermore, we investigate if the combination of decomposed Multiword Expressions (MWEs) can enhance the model learning. MWE integration into MT has seen more than a decade of exploration. However, decomposed MWEs has not previously been explored.
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