Detecting Sentence Boundaries in Sanskrit Texts

Oliver Hellwig


Abstract
The paper applies a deep recurrent neural network to the task of sentence boundary detection in Sanskrit, an important, yet underresourced ancient Indian language. The deep learning approach improves the F scores set by a metrical baseline and by a Conditional Random Field classifier by more than 10%.
Anthology ID:
C16-1028
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
Month:
December
Year:
2016
Address:
Osaka, Japan
Editors:
Yuji Matsumoto, Rashmi Prasad
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
288–297
Language:
URL:
https://aclanthology.org/C16-1028
DOI:
Bibkey:
Cite (ACL):
Oliver Hellwig. 2016. Detecting Sentence Boundaries in Sanskrit Texts. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 288–297, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Detecting Sentence Boundaries in Sanskrit Texts (Hellwig, COLING 2016)
Copy Citation:
PDF:
https://aclanthology.org/C16-1028.pdf