Extending the Use of Adaptor Grammars for Unsupervised Morphological Segmentation of Unseen Languages

Ramy Eskander, Owen Rambow, Tianchun Yang


Abstract
We investigate using Adaptor Grammars for unsupervised morphological segmentation. Using six development languages, we investigate in detail different grammars, the use of morphological knowledge from outside sources, and the use of a cascaded architecture. Using cross-validation on our development languages, we propose a system which is language-independent. We show that it outperforms two state-of-the-art systems on 5 out of 6 languages.
Anthology ID:
C16-1086
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:
900–910
Language:
URL:
https://aclanthology.org/C16-1086
DOI:
Bibkey:
Cite (ACL):
Ramy Eskander, Owen Rambow, and Tianchun Yang. 2016. Extending the Use of Adaptor Grammars for Unsupervised Morphological Segmentation of Unseen Languages. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 900–910, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Extending the Use of Adaptor Grammars for Unsupervised Morphological Segmentation of Unseen Languages (Eskander et al., COLING 2016)
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PDF:
https://aclanthology.org/C16-1086.pdf