Source-Word Decomposition for Neural Machine Translation
Joint Authors
Nguyen, Thien
Le, Hoai
Pham, Van-Huy
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-16
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
End-to-end neural machine translation does not require us to have specialized knowledge of investigated language pairs in building an effective system.
On the other hand, feature engineering proves to be vital in other artificial intelligence fields, such as speech recognition and computer vision.
Inspired by works in those fields, in this paper, we propose a novel feature-based translation model by modifying the state-of-the-art transformer model.
Specifically, the encoder of the modified transformer model takes input combinations of linguistic features comprising of lemma, dependency label, part-of-speech tag, and morphological label instead of source words.
The experiment results for the Russian-Vietnamese language pair show that the proposed feature-based transformer model improves over the strongest baseline transformer translation model by impressive 4.83 BLEU.
In addition, experiment analysis reveals that human judgment on the translation results strongly confirms machine judgment.
Our model could be useful in building translation systems translating from a highly inflectional language into a noninflectional language.
American Psychological Association (APA)
Nguyen, Thien& Le, Hoai& Pham, Van-Huy. 2020. Source-Word Decomposition for Neural Machine Translation. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1195429
Modern Language Association (MLA)
Nguyen, Thien…[et al.]. Source-Word Decomposition for Neural Machine Translation. Mathematical Problems in Engineering No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1195429
American Medical Association (AMA)
Nguyen, Thien& Le, Hoai& Pham, Van-Huy. Source-Word Decomposition for Neural Machine Translation. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1195429
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1195429