English

The NYU-CUBoulder Systems for SIGMORPHON 2020 Task 0 and Task 2

Computation and Language 2020-06-23 v1 Machine Learning

Abstract

We describe the NYU-CUBoulder systems for the SIGMORPHON 2020 Task 0 on typologically diverse morphological inflection and Task 2 on unsupervised morphological paradigm completion. The former consists of generating morphological inflections from a lemma and a set of morphosyntactic features describing the target form. The latter requires generating entire paradigms for a set of given lemmas from raw text alone. We model morphological inflection as a sequence-to-sequence problem, where the input is the sequence of the lemma's characters with morphological tags, and the output is the sequence of the inflected form's characters. First, we apply a transformer model to the task. Second, as inflected forms share most characters with the lemma, we further propose a pointer-generator transformer model to allow easy copying of input characters. Our best performing system for Task 0 is placed 6th out of 23 systems. We further use our inflection systems as subcomponents of approaches for Task 2. Our best performing system for Task 2 is the 2nd best out of 7 submissions.

Cite

@article{arxiv.2006.11830,
  title  = {The NYU-CUBoulder Systems for SIGMORPHON 2020 Task 0 and Task 2},
  author = {Assaf Singer and Katharina Kann},
  journal= {arXiv preprint arXiv:2006.11830},
  year   = {2020}
}

Comments

8 pages, 2 figures

R2 v1 2026-06-23T16:29:51.057Z