Graph Algorithms for Multiparallel Word Alignment

Ayyoob ImaniGooghari, Masoud Jalili Sabet, Lutfi Kerem Senel, Philipp Dufter, François Yvon, Hinrich Schütze


Abstract
With the advent of end-to-end deep learning approaches in machine translation, interest in word alignments initially decreased; however, they have again become a focus of research more recently. Alignments are useful for typological research, transferring formatting like markup to translated texts, and can be used in the decoding of machine translation systems. At the same time, massively multilingual processing is becoming an important NLP scenario, and pretrained language and machine translation models that are truly multilingual are proposed. However, most alignment algorithms rely on bitexts only and do not leverage the fact that many parallel corpora are multiparallel. In this work, we exploit the multiparallelity of corpora by representing an initial set of bilingual alignments as a graph and then predicting additional edges in the graph. We present two graph algorithms for edge prediction: one inspired by recommender systems and one based on network link prediction. Our experimental results show absolute improvements in F1 of up to 28% over the baseline bilingual word aligner in different datasets.
Anthology ID:
2021.emnlp-main.665
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
8457–8469
Language:
URL:
https://aclanthology.org/2021.emnlp-main.665
DOI:
10.18653/v1/2021.emnlp-main.665
Bibkey:
Cite (ACL):
Ayyoob ImaniGooghari, Masoud Jalili Sabet, Lutfi Kerem Senel, Philipp Dufter, François Yvon, and Hinrich Schütze. 2021. Graph Algorithms for Multiparallel Word Alignment. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 8457–8469, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Graph Algorithms for Multiparallel Word Alignment (ImaniGooghari et al., EMNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.emnlp-main.665.pdf
Video:
 https://aclanthology.org/2021.emnlp-main.665.mp4
Code
 cisnlp/graph-align