Graph Algorithms for Multiparallel Word Alignment

Imani, Ayyoob; Sabet, Masoud Jalili; Senel, Lütfi Kerem; Dufter, Philipp; Yvon, François und Schütze, Hinrich (November 2021): Graph Algorithms for Multiparallel Word Alignment. 2021 Conference on Empirical Methods in Natural Language Processing, Online and Punta Cana, Dominican Republic, November 7-11, 2021. Moens, Marie-Francine; Huang, Xuanjing; Specia, Lucia und Yih, Scott Wen-tau (Hrsg.): In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Stroudsburg, PA: Association for Computational Linguistics. S. 8457-8469

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.

• Dokumententyp: Konferenzbeitrag (Paper)
• EU Funded Grant Agreement Number: 740516
• EU-Projekte: Horizon 2020 > ERC Grants > ERC Advanced Grant > ERC Grant 740516: NonSequeToR - Non-sequence models for tokenization replacement
• Fakultätsübergreifende Einrichtungen: Centrum für Informations- und Sprachverarbeitung (CIS)
• Themengebiete: 000 Informatik, Informationswissenschaft, allgemeine Werke > 000 Informatik, Wissen, Systeme ; 400 Sprache > 400 Sprache ; 400 Sprache > 410 Linguistik
• Ort: Stroudsburg, PA
• Sprache: Englisch