CroCoAlign: A Cross-Lingual, Context-Aware and Fully-Neural Sentence Alignment System for Long Texts

Francesco Molfese, Andrei Bejgu, Simone Tedeschi, Simone Conia, Roberto Navigli


Abstract
Sentence alignment – establishing links between corresponding sentences in two related documents – is an important NLP task with several downstream applications, such as machine translation (MT). Despite the fact that existing sentence alignment systems have achieved promising results, their effectiveness is based on auxiliary information such as document metadata or machine-generated translations, as well as hyperparameter-sensitive techniques. Moreover, these systems often overlook the crucial role that context plays in the alignment process. In this paper, we address the aforementioned issues and propose CroCoAlign: the first context-aware, end-to-end and fully neural architecture for sentence alignment. Our system maps source and target sentences in long documents by contextualizing their sentence embeddings with respect to the other sentences in the document. We extensively evaluate CroCoAlign on a multilingual dataset consisting of 20 language pairs derived from the Opus project, and demonstrate that our model achieves state-of-the-art performance. To ensure reproducibility, we release our code and model checkpoints at https://github.com/Babelscape/CroCoAlign.
Anthology ID:
2024.eacl-long.135
Original:
2024.eacl-long.135v1
Version 2:
2024.eacl-long.135v2
Volume:
Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
March
Year:
2024
Address:
St. Julian’s, Malta
Editors:
Yvette Graham, Matthew Purver
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2209–2220
Language:
URL:
https://aclanthology.org/2024.eacl-long.135
DOI:
Bibkey:
Cite (ACL):
Francesco Molfese, Andrei Bejgu, Simone Tedeschi, Simone Conia, and Roberto Navigli. 2024. CroCoAlign: A Cross-Lingual, Context-Aware and Fully-Neural Sentence Alignment System for Long Texts. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2209–2220, St. Julian’s, Malta. Association for Computational Linguistics.
Cite (Informal):
CroCoAlign: A Cross-Lingual, Context-Aware and Fully-Neural Sentence Alignment System for Long Texts (Molfese et al., EACL 2024)
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PDF:
https://aclanthology.org/2024.eacl-long.135.pdf
Video:
 https://aclanthology.org/2024.eacl-long.135.mp4