Low-Resource Corpus Filtering Using Multilingual Sentence Embeddings
Vishrav Chaudhary, Yuqing Tang, Francisco Guzmán, Holger Schwenk, Philipp Koehn
Abstract
In this paper, we describe our submission to the WMT19 low-resource parallel corpus filtering shared task. Our main approach is based on the LASER toolkit (Language-Agnostic SEntence Representations), which uses an encoder-decoder architecture trained on a parallel corpus to obtain multilingual sentence representations. We then use the representations directly to score and filter the noisy parallel sentences without additionally training a scoring function. We contrast our approach to other promising methods and show that LASER yields strong results. Finally, we produce an ensemble of different scoring methods and obtain additional gains. Our submission achieved the best overall performance for both the Nepali-English and Sinhala-English 1M tasks by a margin of 1.3 and 1.4 BLEU respectively, as compared to the second best systems. Moreover, our experiments show that this technique is promising for low and even no-resource scenarios.- Anthology ID:
- W19-5435
- Volume:
- Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2)
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Marco Turchi, Karin Verspoor
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 261–266
- Language:
- URL:
- https://aclanthology.org/W19-5435
- DOI:
- 10.18653/v1/W19-5435
- Cite (ACL):
- Vishrav Chaudhary, Yuqing Tang, Francisco Guzmán, Holger Schwenk, and Philipp Koehn. 2019. Low-Resource Corpus Filtering Using Multilingual Sentence Embeddings. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 261–266, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Low-Resource Corpus Filtering Using Multilingual Sentence Embeddings (Chaudhary et al., WMT 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/W19-5435.pdf