Morphological reinflection with weighted finite-state transducers

Alice Kwak, Michael Hammond, Cheyenne Wing

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationACL 2023 - 20th SIGMORPHON Workshop on Computational Morphology, Phonology, and Phonetics, CMPP 2023
EditorsGarrett Nicolai, Eleanor Chodroff, Cagri Coltekin, Fred Mailhot
PublisherAssociation for Computational Linguistics (ACL)
Pages132-137
Number of pages6
ISBN (Electronic)9781959429937
StatePublished - 2023
Event20th SIGMORPHON Workshop on Computational Morphology, Phonology, and Phonetics, CMPP 2023, as part of ACL 2023 - Toronto, Canada
Duration: Jul 14 2023 → …

Publication series

NameProceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)0736-587X

Conference

Conference20th SIGMORPHON Workshop on Computational Morphology, Phonology, and Phonetics, CMPP 2023, as part of ACL 2023
Country/TerritoryCanada
CityToronto
Period7/14/23 → …

ASJC Scopus subject areas

  • Computer Science Applications
  • Linguistics and Language
  • Language and Linguistics

Fingerprint

Dive into the research topics of 'Morphological reinflection with weighted finite-state transducers'. Together they form a unique fingerprint.

Cite this