To compress or not to compress? A Finite-State approach to Nen verbal morphology

Saliha Muradoglu, Nicholas Evans, Hanna Suominen


Abstract
This paper describes the development of a verbal morphological parser for an under-resourced Papuan language, Nen. Nen verbal morphology is particularly complex, with a transitive verb taking up to 1,740 unique features. The structural properties exhibited by Nen verbs raises interesting choices for analysis. Here we compare two possible methods of analysis: ‘Chunking’ and decomposition. ‘Chunking’ refers to the concept of collating morphological segments into one, whereas the decomposition model follows a more classical linguistic approach. Both models are built using the Finite-State Transducer toolkit foma. The resultant architecture shows differences in size and structural clarity. While the ‘Chunking’ model is under half the size of the full de-composed counterpart, the decomposition displays higher structural order. In this paper, we describe the challenges encountered when modelling a language exhibiting distributed exponence and present the first morphological analyser for Nen, with an overall accuracy of 80.3%.
Anthology ID:
2020.acl-srw.28
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
Month:
July
Year:
2020
Address:
Online
Editors:
Shruti Rijhwani, Jiangming Liu, Yizhong Wang, Rotem Dror
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
207–213
Language:
URL:
https://aclanthology.org/2020.acl-srw.28
DOI:
10.18653/v1/2020.acl-srw.28
Bibkey:
Cite (ACL):
Saliha Muradoglu, Nicholas Evans, and Hanna Suominen. 2020. To compress or not to compress? A Finite-State approach to Nen verbal morphology. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, pages 207–213, Online. Association for Computational Linguistics.
Cite (Informal):
To compress or not to compress? A Finite-State approach to Nen verbal morphology (Muradoglu et al., ACL 2020)
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PDF:
https://aclanthology.org/2020.acl-srw.28.pdf
Video:
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