Using Dependency Tree Grammar To Enhance the Reordering Model of Statistical Machine Translation Systems
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نویسنده
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Rahimi Zahra ,Khadivi Shahram ,Faili Heshaam
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منبع
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International Journal Of Information And Communication Technology Research - 2014 - دوره : 6 - شماره : 4 - صفحه:57 -67
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چکیده
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We propose three novel reordering models for statistical machine translation. these reordering models use dependency tree to improve the translation quality. all reordering models are utilized as features in a log linear framework and therefore guide the decoder to make better decisions about reordering. these reordering models are tested on two english-persian parallel corpora with different statistics and domains. the bleu score is improved by 2.5 on the first corpus and by 1.2 on the other.
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کلیدواژه
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Statistical Machine Translation; Reordering Model; Dependency Tree; Discriminative Reordering Model; Discriminative Decoder; Long Range Reordering; Maximum Entropy; Distortion Model
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آدرس
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Amirkabir University Of Technology, Human Language Technology Lab, ایران, Amirkabir University Of Technology, Human Language Technology Lab, ایران, University Of Tehran, Electrical And Computer Engineering Department, ایران
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