Vecalign: Improved Sentence Alignment in Linear Time and Space

Brian Thompson, Philipp Koehn


Abstract
We introduce Vecalign, a novel bilingual sentence alignment method which is linear in time and space with respect to the number of sentences being aligned and which requires only bilingual sentence embeddings. On a standard German–French test set, Vecalign outperforms the previous state-of-the-art method (which has quadratic time complexity and requires a machine translation system) by 5 F1 points. It substantially outperforms the popular Hunalign toolkit at recovering Bible verse alignments in medium- to low-resource language pairs, and it improves downstream MT quality by 1.7 and 1.6 BLEU in Sinhala-English and Nepali-English, respectively, compared to the Hunalign-based Paracrawl pipeline.
Anthology ID:
D19-1136
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
1342–1348
Language:
URL:
https://aclanthology.org/D19-1136
DOI:
10.18653/v1/D19-1136
Bibkey:
Cite (ACL):
Brian Thompson and Philipp Koehn. 2019. Vecalign: Improved Sentence Alignment in Linear Time and Space. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 1342–1348, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Vecalign: Improved Sentence Alignment in Linear Time and Space (Thompson & Koehn, EMNLP 2019)
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PDF:
https://aclanthology.org/D19-1136.pdf