Improving the Morphological Analysis of Classical Sanskrit

Oliver Hellwig


Abstract
The paper describes a new tagset for the morphological disambiguation of Sanskrit, and compares the accuracy of two machine learning methods (Conditional Random Fields, deep recurrent neural networks) for this task, with a special focus on how to model the lexicographic information. It reports a significant improvement over previously published results.
Anthology ID:
W16-3715
Volume:
Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016)
Month:
December
Year:
2016
Address:
Osaka, Japan
Venues:
WS | WSSANLP
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
142–151
Language:
URL:
https://aclanthology.org/W16-3715
DOI:
Bibkey:
Cite (ACL):
Oliver Hellwig. 2016. Improving the Morphological Analysis of Classical Sanskrit. In Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016), pages 142–151, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Improving the Morphological Analysis of Classical Sanskrit (Hellwig, 2016)
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PDF:
https://aclanthology.org/W16-3715.pdf