Context-Aware Cross-Lingual Mapping

Hanan Aldarmaki, Mona Diab


Abstract
Cross-lingual word vectors are typically obtained by fitting an orthogonal matrix that maps the entries of a bilingual dictionary from a source to a target vector space. Word vectors, however, are most commonly used for sentence or document-level representations that are calculated as the weighted average of word embeddings. In this paper, we propose an alternative to word-level mapping that better reflects sentence-level cross-lingual similarity. We incorporate context in the transformation matrix by directly mapping the averaged embeddings of aligned sentences in a parallel corpus. We also implement cross-lingual mapping of deep contextualized word embeddings using parallel sentences with word alignments. In our experiments, both approaches resulted in cross-lingual sentence embeddings that outperformed context-independent word mapping in sentence translation retrieval. Furthermore, the sentence-level transformation could be used for word-level mapping without loss in word translation quality.
Anthology ID:
N19-1391
Volume:
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3906–3911
Language:
URL:
https://aclanthology.org/N19-1391
DOI:
10.18653/v1/N19-1391
Bibkey:
Cite (ACL):
Hanan Aldarmaki and Mona Diab. 2019. Context-Aware Cross-Lingual Mapping. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 3906–3911, Minneapolis, Minnesota. Association for Computational Linguistics.
Cite (Informal):
Context-Aware Cross-Lingual Mapping (Aldarmaki & Diab, NAACL 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/auto-file-uploads/N19-1391.pdf
Code
 h-aldarmaki/sent_translation_retrieval