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.- Anthology ID:
- 2022.eamt-1.34
- Volume:
- Proceedings of the 23rd Annual Conference of the European Association for Machine Translation
- Month:
- June
- Year:
- 2022
- Address:
- Ghent, Belgium
- Editors:
- Helena Moniz, Lieve Macken, Andrew Rufener, Loïc Barrault, Marta R. Costa-jussà, Christophe Declercq, Maarit Koponen, Ellie Kemp, Spyridon Pilos, Mikel L. Forcada, Carolina Scarton, Joachim Van den Bogaert, Joke Daems, Arda Tezcan, Bram Vanroy, Margot Fonteyne
- Venue:
- EAMT
- SIG:
- Publisher:
- European Association for Machine Translation
- Note:
- Pages:
- 289–290
- Language:
- URL:
- https://aclanthology.org/2022.eamt-1.34
- DOI:
- Bibkey:
- Cite (ACL):
- Joke Daems 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, pages 289–290, Ghent, Belgium. European Association for Machine Translation.
- Cite (Informal):
- DeBiasByUs: Raising Awareness and Creating a Database of MT Bias (Daems & Hackenbuchner, EAMT 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.eamt-1.34.pdf
Export citation
@inproceedings{daems-hackenbuchner-2022-debiasbyus,
title = "{D}e{B}ias{B}y{U}s: Raising Awareness and Creating a Database of {MT} Bias",
author = "Daems, Joke and
Hackenbuchner, Jani{\c{c}}a",
editor = {Moniz, Helena and
Macken, Lieve and
Rufener, Andrew and
Barrault, Lo{\"\i}c and
Costa-juss{\`a}, Marta R. and
Declercq, Christophe and
Koponen, Maarit and
Kemp, Ellie and
Pilos, Spyridon and
Forcada, Mikel L. and
Scarton, Carolina and
Van den Bogaert, Joachim and
Daems, Joke and
Tezcan, Arda and
Vanroy, Bram and
Fonteyne, Margot},
booktitle = "Proceedings of the 23rd Annual Conference of the European Association for Machine Translation",
month = jun,
year = "2022",
address = "Ghent, Belgium",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/2022.eamt-1.34",
pages = "289--290",
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.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="daems-hackenbuchner-2022-debiasbyus">
<titleInfo>
<title>DeBiasByUs: Raising Awareness and Creating a Database of MT Bias</title>
</titleInfo>
<name type="personal">
<namePart type="given">Joke</namePart>
<namePart type="family">Daems</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Janiça</namePart>
<namePart type="family">Hackenbuchner</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2022-06</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 23rd Annual Conference of the European Association for Machine Translation</title>
</titleInfo>
<name type="personal">
<namePart type="given">Helena</namePart>
<namePart type="family">Moniz</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Lieve</namePart>
<namePart type="family">Macken</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Andrew</namePart>
<namePart type="family">Rufener</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Loïc</namePart>
<namePart type="family">Barrault</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Marta</namePart>
<namePart type="given">R</namePart>
<namePart type="family">Costa-jussà</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Christophe</namePart>
<namePart type="family">Declercq</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Maarit</namePart>
<namePart type="family">Koponen</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ellie</namePart>
<namePart type="family">Kemp</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Spyridon</namePart>
<namePart type="family">Pilos</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mikel</namePart>
<namePart type="given">L</namePart>
<namePart type="family">Forcada</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Carolina</namePart>
<namePart type="family">Scarton</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Joachim</namePart>
<namePart type="family">Van den Bogaert</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Joke</namePart>
<namePart type="family">Daems</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Arda</namePart>
<namePart type="family">Tezcan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Bram</namePart>
<namePart type="family">Vanroy</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Margot</namePart>
<namePart type="family">Fonteyne</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>European Association for Machine Translation</publisher>
<place>
<placeTerm type="text">Ghent, Belgium</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<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.</abstract>
<identifier type="citekey">daems-hackenbuchner-2022-debiasbyus</identifier>
<location>
<url>https://aclanthology.org/2022.eamt-1.34</url>
</location>
<part>
<date>2022-06</date>
<extent unit="page">
<start>289</start>
<end>290</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings %T DeBiasByUs: Raising Awareness and Creating a Database of MT Bias %A Daems, Joke %A Hackenbuchner, Janiça %Y Moniz, Helena %Y Macken, Lieve %Y Rufener, Andrew %Y Barrault, Loïc %Y Costa-jussà, Marta R. %Y Declercq, Christophe %Y Koponen, Maarit %Y Kemp, Ellie %Y Pilos, Spyridon %Y Forcada, Mikel L. %Y Scarton, Carolina %Y Van den Bogaert, Joachim %Y Daems, Joke %Y Tezcan, Arda %Y Vanroy, Bram %Y Fonteyne, Margot %S Proceedings of the 23rd Annual Conference of the European Association for Machine Translation %D 2022 %8 June %I European Association for Machine Translation %C Ghent, Belgium %F daems-hackenbuchner-2022-debiasbyus %X 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. %U https://aclanthology.org/2022.eamt-1.34 %P 289-290
Markdown (Informal)
[DeBiasByUs: Raising Awareness and Creating a Database of MT Bias](https://aclanthology.org/2022.eamt-1.34) (Daems & Hackenbuchner, EAMT 2022)
- DeBiasByUs: Raising Awareness and Creating a Database of MT Bias (Daems & Hackenbuchner, EAMT 2022)
ACL
- Joke Daems 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, pages 289–290, Ghent, Belgium. European Association for Machine Translation.