TY  - CONF
ID  - SisLab1549
UR  - https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1549/
A1  - Tran, Hong Viet
A1  - Nguyen, Van Vinh
A1  - Nguyen, Le Minh
Y1  - 2016/03/26/
N2  - 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.
TI  - Improving English-Vietnamese Statistical Machine Translation Using Preprocessing Dependency Syntactic
M2  - Hanoi
AV  - public
T2  - SW4PHD: the 2016 Scientific Workshop for PhD Students
ER  -