Gender-Inclusive Grammatical Error Correction through Augmentation

Gunnar Lund, Kostiantyn Omelianchuk, Igor Samokhin
6/12/2023
cs.CL

No official code found. Best implementation: grammarly/gender-inclusive-gec (8 stars, last commit 2023-07-28).

Abstract

In this paper we show that GEC systems display gender bias related to the use of masculine and feminine terms and the gender-neutral singular "they". We develop parallel datasets of texts with masculine and feminine terms and singular "they" and use them to quantify gender bias in three competitive GEC systems. We contribute a novel data augmentation technique for singular "they" leveraging linguistic insights about its distribution relative to plural "they". We demonstrate that both this data augmentation technique and a refinement of a similar augmentation technique for masculine and feminine terms can generate training data that reduces bias in GEC systems, especially with respect to singular "they" while maintaining the same level of quality.

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Code Implementations(1)

grammarly/gender-inclusive-gecCommunity100%
80Python, Macaulay2May 30, 20233 years ago

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Cite this paper

@article{lund2023genderinclusive,
  title  = {Gender-Inclusive Grammatical Error Correction through Augmentation},
  author = {Gunnar Lund and Kostiantyn Omelianchuk and Igor Samokhin},
  year   = {2023},
  eprint = {2306.07415},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.07415v1}
}

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