Graph Neural Networks for Multiparallel Word Alignment

Imani, Ayyoob; Senel, Lütfi Kerem; Sabet, Masoud Jalili; Yvon, François and Schütze, Hinrich (May 2022): Graph Neural Networks for Multiparallel Word Alignment. ACL 2022, Dublin, Ireland, May 2022. Muresan, Smaranda; Nakov, Preslav and Villavicencio, Aline (eds.) : In: Findings of the Association for Computational Linguistics: ACL 2022, Stroudsburg, PA: Association for Computational Linguistics. 1384 -1396

Abstract

After a period of decrease, interest in word alignments is increasing again for their usefulness in domains such as typological research, cross-lingual annotation projection and machine translation. Generally, alignment algorithms only use bitext and do not make use of the fact that many parallel corpora are multiparallel. Here, we compute high-quality word alignments between multiple language pairs by considering all language pairs together. First, we create a multiparallel word alignment graph, joining all bilingual word alignment pairs in one graph. Next, we use graph neural networks (GNNs) to exploit the graph structure. Our GNN approach (i) utilizes information about the meaning, position and language of the input words, (ii) incorporates information from multiple parallel sentences, (iii) adds and removes edges from the initial alignments, and (iv) yields a prediction model that can generalize beyond the training sentences. We show that community detection algorithms can provide valuable information for multiparallel word alignment. Our method outperforms previous work on three word alignment datasets and on a downstream task.

• Item Type: Conference or Workshop Item (Paper)
• EU Funded Grant Agreement Number: 740516
• EU Projects: Horizon 2020 > ERC Grants > ERC Advanced Grant > ERC Grant 740516: NonSequeToR - Non-sequence models for tokenization replacement
• Research Centers: Center for Information and Language Processing (CIS)
• Subjects: 000 Computer science, information and general works > 000 Computer science, knowledge, and systems; 400 Language > 400 Language; 400 Language > 410 Linguistics
• Place of Publication: Stroudsburg, PA
• Language: English