Morphological reinflection with weighted finite-state transducers
Alice Saebom Kwak, Michael Hammond, Cheyenne Wing · 2023
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.