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Improving English-Vietnamese Statistical Machine Translation Using Preprocessing Dependency Syntactic

Hong Viet Tran and Van Vinh Nguyen and Le Minh Nguyen (2016) Improving English-Vietnamese Statistical Machine Translation Using Preprocessing Dependency Syntactic. In: SW4PHD: the 2016 Scientific Workshop for PhD Students, 26 March 2016, Hanoi.

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Abstract

In this paper, we would like to present a new reordering approach based on a dependency parser in phrase based statistical machine translation (SMT) for English to Vietnamese. The proposed method can efficiently incorporate linguistic knowledge into SMT systems. We inspired from [1] using preprocessing reordering approaches. Dependency parser and transformation rules are used to reorder the source sentence and applied for systems translating English to Vietnamese. The experiment results showed that the proposed approach achieved improvements in BLEU scores over MOSES which is the state-of-the art phrase based SMT system.

Item Type:Conference or Workshop Item (Poster)
Subjects:Information Technology (IT)
Divisions:Faculty of Information Technology (FIT)
ID Code:1549
Deposited By: Dr Ngoc Thang Bui
Deposited On:23 May 2016 03:01
Last Modified:23 May 2016 03:01

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