Abstract
The WMT19 Parallel Corpus Filtering For Low-Resource Conditions Task aims to test various methods of filtering a noisy parallel corpora, to make them useful for training machine translation systems. This year the noisy corpora are the relatively low-resource language pairs of Nepali-English and Sinhala-English. This papers describes the Air Force Research Laboratory (AFRL) submissions, including preprocessing methods and scoring metrics. Numerical results indicate a benefit over baseline and the relative benefits of different options.- Anthology ID:
- W19-5436
- Volume:
- Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2)
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 267–270
- Language:
- URL:
- https://aclanthology.org/W19-5436
- DOI:
- 10.18653/v1/W19-5436
- Cite (ACL):
- Grant Erdmann and Jeremy Gwinnup. 2019. Quality and Coverage: The AFRL Submission to the WMT19 Parallel Corpus Filtering for Low-Resource Conditions Task. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 267–270, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Quality and Coverage: The AFRL Submission to the WMT19 Parallel Corpus Filtering for Low-Resource Conditions Task (Erdmann & Gwinnup, WMT 2019)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/W19-5436.pdf