Abstract
This paper describes the submission by the University of Arizona to the SIGMORPHON 2023 Shared Task on typologically diverse morphological (re-)infection. In our submission, we investigate the role of frequency, length, and weighted transducers in addressing the challenge of morphological reinflection. We start with the non-neural baseline provided for the task and show how some improvement can be gained by integrating length and frequency in prefix selection. We also investigate using weighted finite-state transducers, jump-started from edit distance and directly augmented with frequency. Our specific technique is promising and quite simple, but we see only modest improvements for some languages here.- Anthology ID:
- 2023.sigmorphon-1.15
- Volume:
- Proceedings of the 20th SIGMORPHON workshop on Computational Research in Phonetics, Phonology, and Morphology
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Garrett Nicolai, Eleanor Chodroff, Frederic Mailhot, Çağrı Çöltekin
- Venue:
- SIGMORPHON
- SIG:
- SIGMORPHON
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 132–137
- Language:
- URL:
- https://aclanthology.org/2023.sigmorphon-1.15
- DOI:
- 10.18653/v1/2023.sigmorphon-1.15
- Cite (ACL):
- Alice Kwak, Michael Hammond, and Cheyenne Wing. 2023. Morphological reinflection with weighted finite-state transducers. In Proceedings of the 20th SIGMORPHON workshop on Computational Research in Phonetics, Phonology, and Morphology, pages 132–137, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Morphological reinflection with weighted finite-state transducers (Kwak et al., SIGMORPHON 2023)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2023.sigmorphon-1.15.pdf