Abstract
This work examines CRF-based sequence alignment models for learning natural language morphology. Although these systems have performed well for a limited number of languages, this work, as part of the SIGMORPHON 2016 shared task, specifically sets out to determine whether these models handle non-concatenative morphology as well as previous work might suggest. Results, however, indicate a strong preference for simpler, concatenative morphological systems.
Cite
CITATION STYLE
King, D. L. (2016). Evaluating sequence alignment for learning inflectional morphology. In Proceedings of the 14th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology, SIGMORPHON 2016 at the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 (pp. 49–53). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w16-2008
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