NICT’s Corpus Filtering Systems for the WMT18 Parallel Corpus Filtering Task

Rui Wang, Benjamin Marie, Masao Utiyama, Eiichiro Sumita


Abstract
This paper presents the NICT’s participation in the WMT18 shared parallel corpus filtering task. The organizers provided 1 billion words German-English corpus crawled from the web as part of the Paracrawl project. This corpus is too noisy to build an acceptable neural machine translation (NMT) system. Using the clean data of the WMT18 shared news translation task, we designed several features and trained a classifier to score each sentence pairs in the noisy data. Finally, we sampled 100 million and 10 million words and built corresponding NMT systems. Empirical results show that our NMT systems trained on sampled data achieve promising performance.
Anthology ID:
W18-6489
Volume:
Proceedings of the Third Conference on Machine Translation: Shared Task Papers
Month:
October
Year:
2018
Address:
Belgium, Brussels
Venues:
EMNLP | WMT | WS
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
963–967
Language:
URL:
https://www.aclweb.org/anthology/W18-6489
DOI:
10.18653/v1/W18-6489
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-6489.pdf