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DeBiasByUs : raising awareness and creating a database of MT bias

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Abstract
This paper presents the project initiated by the BiasByUs team resulting from the 2021 Artificially Correct Hackaton. We briefly explain our winning participation in the hackaton, tackling the challenge on ‘Database and detection of gender bi-as in A.I. translations’, we highlight the importance of gender bias in Machine Translation (MT), and describe our pro-posed solution to the challenge, the cur-rent status of the project, and our envi-sioned future collaborations and re-search.

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MLA
Daems, Joke, and Janiça Hackenbuchner. “DeBiasByUs : Raising Awareness and Creating a Database of MT Bias.” Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, edited by Lieve Macken et al., European Association for Machine Translation, 2022, pp. 289–90.
APA
Daems, J., & Hackenbuchner, J. (2022). DeBiasByUs : raising awareness and creating a database of MT bias. In L. Macken, A. Rufener, J. Van den Bogaert, J. Daems, A. Tezcan, B. Vanroy, … H. Moniz (Eds.), Proceedings of the 23rd Annual Conference of the European Association for Machine Translation (pp. 289–290). Ghent, Belgium: European Association for Machine Translation.
Chicago author-date
Daems, Joke, and Janiça Hackenbuchner. 2022. “DeBiasByUs : Raising Awareness and Creating a Database of MT Bias.” In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, edited by Lieve Macken, Andrew Rufener, Joachim Van den Bogaert, Joke Daems, Arda Tezcan, Bram Vanroy, Margot Fonteyne, et al., 289–90. Ghent, Belgium: European Association for Machine Translation.
Chicago author-date (all authors)
Daems, Joke, and Janiça Hackenbuchner. 2022. “DeBiasByUs : Raising Awareness and Creating a Database of MT Bias.” In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, ed by. Lieve Macken, Andrew Rufener, Joachim Van den Bogaert, Joke Daems, Arda Tezcan, Bram Vanroy, Margot Fonteyne, Loïc Barrault, Marta R. Costa-jussà, Ellie Kemp, Spyridon Pilos, Christophe Declercq, Maarit Koponen, Mikel L. Forcada, Carolina Scarton, and Helena Moniz, 289–290. Ghent, Belgium: European Association for Machine Translation.
Vancouver
1.
Daems J, Hackenbuchner J. DeBiasByUs : raising awareness and creating a database of MT bias. In: Macken L, Rufener A, Van den Bogaert J, Daems J, Tezcan A, Vanroy B, et al., editors. Proceedings of the 23rd Annual Conference of the European Association for Machine Translation. Ghent, Belgium: European Association for Machine Translation; 2022. p. 289–90.
IEEE
[1]
J. Daems and J. Hackenbuchner, “DeBiasByUs : raising awareness and creating a database of MT bias,” in Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, Ghent, Belgium, 2022, pp. 289–290.
@inproceedings{8761022,
  abstract     = {{This paper presents the project initiated by the BiasByUs team resulting from the 2021 Artificially Correct Hackaton. We briefly explain our winning participation in the hackaton, tackling the challenge on ‘Database and detection of gender bi-as in A.I. translations’, we highlight the importance of gender bias in Machine Translation (MT), and describe our pro-posed solution to the challenge, the cur-rent status of the project, and our envi-sioned future collaborations and re-search.}},
  author       = {{Daems, Joke and Hackenbuchner, Janiça}},
  booktitle    = {{Proceedings of the 23rd Annual Conference of the European Association for Machine Translation}},
  editor       = {{Macken, Lieve and Rufener, Andrew and Van den Bogaert, Joachim and Daems, Joke and Tezcan, Arda and Vanroy, Bram and Fonteyne, Margot and Barrault, Loïc and Costa-jussà, Marta R. and Kemp, Ellie and Pilos, Spyridon and Declercq, Christophe and Koponen, Maarit and Forcada, Mikel L. and Scarton, Carolina and Moniz, Helena}},
  isbn         = {{9789464597622}},
  language     = {{eng}},
  location     = {{Ghent, Belgium}},
  pages        = {{289--290}},
  publisher    = {{European Association for Machine Translation}},
  title        = {{DeBiasByUs : raising awareness and creating a database of MT bias}},
  url          = {{https://aclanthology.org/2022.eamt-1.34}},
  year         = {{2022}},
}