SYSTRAN @ WAT 2019: Russian-Japanese News Commentary task

Jitao Xu, TuAnh Nguyen, MinhQuang Pham, Josep Crego, Jean Senellart


Abstract
This paper describes Systran’s submissions to WAT 2019 Russian-Japanese News Commentary task. A challenging translation task due to the extremely low resources available and the distance of the language pair. We have used the neural Transformer architecture learned over the provided resources and we carried out synthetic data generation experiments which aim at alleviating the data scarcity problem. Results indicate the suitability of the data augmentation experiments, enabling our systems to rank first according to automatic evaluations.
Anthology ID:
D19-5225
Volume:
Proceedings of the 6th Workshop on Asian Translation
Month:
November
Year:
2019
Address:
Hong Kong, China
Venues:
EMNLP | WAT | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
189–194
Language:
URL:
https://www.aclweb.org/anthology/D19-5225
DOI:
10.18653/v1/D19-5225
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PDF:
http://aclanthology.lst.uni-saarland.de/D19-5225.pdf