NeuTral Rewriter: A Rule-Based and Neural Approach to Automatic Rewriting into Gender-Neutral Alternatives

Research output: Contribution to conferencePaperScientificpeer-review

Abstract

Recent years have seen an increasing need for gender-neutral and inclusive language. Within the field of NLP, there are various mono- and bilingual use cases where gender inclusive language is appropriate, if not preferred due to ambiguity or uncertainty in terms of the gender of referents. In this work, we present a rule-based and a neural approach to gender-neutral rewriting for English along with manually curated synthetic data (WinoBias+) and natural data (OpenSubtitles and Reddit) benchmarks. A detailed manual and automatic evaluation highlights how our NeuTral Rewriter, trained on data generated by the rule-based approach, obtains word error rates (WER) below 0.18% on synthetic, in-domain and out-domain test sets.
Original languageEnglish
Pages8940–8948
Number of pages8
DOIs
Publication statusPublished - 13 Sep 2021
EventThe 2021 Conference on Empirical Methods in Natural Language Processing - Punta Cana, Punta Cana, Dominica
Duration: 7 Nov 202211 Nov 2022
https://2021.emnlp.org/

Conference

ConferenceThe 2021 Conference on Empirical Methods in Natural Language Processing
Abbreviated titleEMNLP 2021
Country/TerritoryDominica
CityPunta Cana
Period7/11/2211/11/22
Internet address

Keywords

  • cs.CL
  • cs.AI

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