Data Augmentation with Unsupervised Machine Translation Improves the Structural Similarity of Cross-lingual Word Embeddings

Sosuke Nishikawa, Ryokan Ri, Yoshimasa Tsuruoka. Data Augmentation with Unsupervised Machine Translation Improves the Structural Similarity of Cross-lingual Word Embeddings. In Jad Kabbara, Haitao Lin, Amandalynne Paullada, Jannis Vamvas, editors, Proceedings of the ACL-IJCNLP 2021 Student Research Workshop, ACL 2021, Online, JUli 5-10, 2021. pages 163-173, Association for Computational Linguistics, 2021. [doi]

@inproceedings{NishikawaRT21,
  title = {Data Augmentation with Unsupervised Machine Translation Improves the Structural Similarity of Cross-lingual Word Embeddings},
  author = {Sosuke Nishikawa and Ryokan Ri and Yoshimasa Tsuruoka},
  year = {2021},
  url = {https://aclanthology.org/2021.acl-srw.17},
  researchr = {https://researchr.org/publication/NishikawaRT21},
  cites = {0},
  citedby = {0},
  pages = {163-173},
  booktitle = {Proceedings of the ACL-IJCNLP 2021 Student Research Workshop, ACL 2021, Online, JUli 5-10, 2021},
  editor = {Jad Kabbara and Haitao Lin and Amandalynne Paullada and Jannis Vamvas},
  publisher = {Association for Computational Linguistics},
  isbn = {978-1-952148-03-3},
}