SIGMORPHON 2022 Task 0 Submission Description: Modelling Morphological Inflection with Data-Driven and Rule-Based Approaches
Tatiana Merzhevich, Nkonye Gbadegoye, Leander Girrbach, Jingwen Li, Ryan Soh-Eun Shim
Abstract
This paper describes our participation in the 2022 SIGMORPHON-UniMorph Shared Task on Typologically Diverse and AcquisitionInspired Morphological Inflection Generation. We present two approaches: one being a modification of the neural baseline encoderdecoder model, the other being hand-coded morphological analyzers using finite-state tools (FST) and outside linguistic knowledge. While our proposed modification of the baseline encoder-decoder model underperforms the baseline for almost all languages, the FST methods outperform other systems in the respective languages by a large margin. This confirms that purely data-driven approaches have not yet reached the maturity to replace trained linguists for documentation and analysis especially considering low-resource and endangered languages.- Anthology ID:
- 2022.sigmorphon-1.20
- Volume:
- Proceedings of the 19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, Washington
- Editors:
- Garrett Nicolai, Eleanor Chodroff
- Venue:
- SIGMORPHON
- SIG:
- SIGMORPHON
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 204–211
- Language:
- URL:
- https://aclanthology.org/2022.sigmorphon-1.20
- DOI:
- 10.18653/v1/2022.sigmorphon-1.20
- Cite (ACL):
- Tatiana Merzhevich, Nkonye Gbadegoye, Leander Girrbach, Jingwen Li, and Ryan Soh-Eun Shim. 2022. SIGMORPHON 2022 Task 0 Submission Description: Modelling Morphological Inflection with Data-Driven and Rule-Based Approaches. In Proceedings of the 19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology, pages 204–211, Seattle, Washington. Association for Computational Linguistics.
- Cite (Informal):
- SIGMORPHON 2022 Task 0 Submission Description: Modelling Morphological Inflection with Data-Driven and Rule-Based Approaches (Merzhevich et al., SIGMORPHON 2022)
- PDF:
- https://preview.aclanthology.org/naacl24-info/2022.sigmorphon-1.20.pdf