Tran Hong, Viet and Nguyen Hoang, Quan and Nguyen Van, Vinh (2018) A Neural Network Classifier Based on Dependency Tree for English-Vietnamese Statistical Machine Translation. In: Cicling 2018. (In Press)
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Abstract
Reordering in MT is a major challenge when translating between languages with different of sentence structures. In Phrase-based statistical machine translation (PBSMT) systems, syntactic pre-ordering is a commonly used preprocessing technique. This technique can be used to adjust the syntax of the source language to that of the target language by changing the word order of a source sentence prior to translation and solving to overcome a weakness of classical phrase-based translation systems: long distance reordering. In this paper, we propose a new pre-ordering approach by defining dependency-based features and using a neural network classifier for reordering the words in the source sentence into the same order in target sentence. Experiments on English-Vietnamese machine translation showed that our approach yielded a statistically significant improvement compared to our prior baseline phrase-based SMT system.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Information Technology (IT) |
| Divisions: | Faculty of Information Technology (FIT) |
| Depositing User: | Nguy�n V |
| Date Deposited: | 25 Dec 2018 11:04 |
| Last Modified: | 25 Dec 2018 11:04 |
| URI: | http://eprints.uet.vnu.edu.vn/eprints/id/eprint/3381 |
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