Morphological Paradigms: Computational Structure and Unsupervised Learning

Jackson L. Lee


Abstract
This thesis explores the computational structure of morphological paradigms from the perspective of unsupervised learning. Three topics are studied: (i) stem identification, (ii) paradigmatic similarity, and (iii) paradigm induction. All the three topics progress in terms of the scope of data in question. The first and second topics explore structure when morphological paradigms are given, first within a paradigm and then across paradigms. The third topic asks where morphological paradigms come from in the first place, and explores strategies of paradigm induction from child-directed speech. This research is of interest to linguists and natural language processing researchers, for both theoretical questions and applied areas.
Anthology ID:
N15-2022
Volume:
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop
Month:
June
Year:
2015
Address:
Denver, Colorado
Editors:
Diana Inkpen, Smaranda Muresan, Shibamouli Lahiri, Karen Mazidi, Alisa Zhila
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
161–167
Language:
URL:
https://preview.aclanthology.org/add-orcids-2023-acl/N15-2022/
DOI:
10.3115/v1/N15-2022
Bibkey:
Cite (ACL):
Jackson L. Lee. 2015. Morphological Paradigms: Computational Structure and Unsupervised Learning. In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop, pages 161–167, Denver, Colorado. Association for Computational Linguistics.
Cite (Informal):
Morphological Paradigms: Computational Structure and Unsupervised Learning (Lee, NAACL 2015)
Copy Citation:
PDF:
https://preview.aclanthology.org/add-orcids-2023-acl/N15-2022.pdf