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
- Editors:
- Jill Burstein, Christy Doran, Thamar Solorio
- 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
- 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)
- PDF:
- https://preview.aclanthology.org/naacl24-info/N19-1391.pdf
- Code
- h-aldarmaki/sent_translation_retrieval