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
- Venue:
- COLING
- SIG:
- Publisher:
- The COLING 2016 Organizing Committee
- Note:
- Pages:
- 288–297
- Language:
- URL:
- https://aclanthology.org/C16-1028
- DOI:
- 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)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/C16-1028.pdf