Evaluating Gender Bias in Hindi-English Machine Translation

Gauri Gupta, Krithika Ramesh, Sanjay Singh

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

3 Citations (Scopus)

Abstract

With language models being deployed increasingly in the real world, it is essential to address the issue of the fairness of their outputs. The word embedding representations of these language models often implicitly draw unwanted associations that form a social bias within the model. The nature of gendered languages like Hindi, poses an additional problem to the quantification and mitigation of bias, owing to the change in the form of the words in the sentence, based on the gender of the subject. Additionally, there is sparse work done in the realm of measuring and debiasing systems for Indic languages. In our work, we attempt to evaluate and quantify the gender bias within a Hindi-English machine translation system.We implement a modified version of the existing TGBI metric based on the grammatical considerations for Hindi. We also compare and contrast the resulting bias measurements across multiple metrics for pre-trained embeddings and the ones learned by our machine translation model.

Original languageEnglish
Title of host publicationGeBNLP 2021 - 3rd Workshop on Gender Bias in Natural Language Processing, Proceedings
EditorsMarta R. Costa-jussa, Hila Gonen, Christian Hardmeier, Christian Hardmeier, Kellie Webster
PublisherAssociation for Computational Linguistics (ACL)
Pages16-23
Number of pages8
ISBN (Electronic)9781954085619
Publication statusPublished - 2021
Event3rd Workshop on Gender Bias in Natural Language Processing, GeBNLP 2021 - Virtual, Online, Thailand
Duration: 05-08-2021 → …

Publication series

NameGeBNLP 2021 - 3rd Workshop on Gender Bias in Natural Language Processing, Proceedings

Conference

Conference3rd Workshop on Gender Bias in Natural Language Processing, GeBNLP 2021
Country/TerritoryThailand
CityVirtual, Online
Period05-08-21 → …

All Science Journal Classification (ASJC) codes

  • Psychology(all)
  • Gender Studies
  • Computer Science Applications
  • Information Systems
  • Computational Theory and Mathematics

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