Can Cognate Prediction Be Modelled as a Low-Resource Machine Translation Task?

Clémentine Fourrier, Rachel Bawden, Benoît Sagot


Anthology ID:
2021.findings-acl.75
Volume:
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
847–861
Language:
URL:
https://aclanthology.org/2021.findings-acl.75
DOI:
10.18653/v1/2021.findings-acl.75
Bibkey:
Cite (ACL):
Clémentine Fourrier, Rachel Bawden, and Benoît Sagot. 2021. Can Cognate Prediction Be Modelled as a Low-Resource Machine Translation Task?. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 847–861, Online. Association for Computational Linguistics.
Cite (Informal):
Can Cognate Prediction Be Modelled as a Low-Resource Machine Translation Task? (Fourrier et al., Findings 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.findings-acl.75.pdf
Code
 clefourrier/coppermt