Itihasa: A large-scale corpus for Sanskrit to English translation

Rahul Aralikatte, Miryam de Lhoneux, Anoop Kunchukuttan, Anders Søgaard


Abstract
This work introduces Itihasa, a large-scale translation dataset containing 93,000 pairs of Sanskrit shlokas and their English translations. The shlokas are extracted from two Indian epics viz., The Ramayana and The Mahabharata. We first describe the motivation behind the curation of such a dataset and follow up with empirical analysis to bring out its nuances. We then benchmark the performance of standard translation models on this corpus and show that even state-of-the-art transformer architectures perform poorly, emphasizing the complexity of the dataset.
Anthology ID:
2021.wat-1.22
Original:
2021.wat-1.22v1
Version 2:
2021.wat-1.22v2
Volume:
Proceedings of the 8th Workshop on Asian Translation (WAT2021)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP | WAT
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
191–197
Language:
URL:
https://aclanthology.org/2021.wat-1.22
DOI:
10.18653/v1/2021.wat-1.22
Bibkey:
Cite (ACL):
Rahul Aralikatte, Miryam de Lhoneux, Anoop Kunchukuttan, and Anders Søgaard. 2021. Itihasa: A large-scale corpus for Sanskrit to English translation. In Proceedings of the 8th Workshop on Asian Translation (WAT2021), pages 191–197, Online. Association for Computational Linguistics.
Cite (Informal):
Itihasa: A large-scale corpus for Sanskrit to English translation (Aralikatte et al., WAT 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.wat-1.22.pdf
Data
Itihasa