1,721,072 research outputs found
Gender-inclusive translation for a gender-inclusive sport : strategies and translator perceptions at the International Quadball Association
No full textGender-inclusive language is of key importance to the IQA, the international governing body for quadball, a mixed-gender contact sport that explicitly welcomes players of all genders. While relatively straightforward for English, the picture becomes more complicated for most of the other IQA working languages. This paper provides an overview of the strategies currently chosen by translation team leaders for different IQA languages, the factors that influenced this decision and their connection with existing research on inclusive language strategies. It further explores the awareness and attitudes of IQA translators towards those strategies and factors
Pilot testing gender-inclusive translations and machine translations for German quadball referee certification test takers
No full textGender-inclusive translations are the default at the International Quadball Association, yet translators make different choices for the (timed) referee certification tests to improve readability. However, the actual impact of a strategy on readability and performance has not been tested. This pilot study explores the impact of translation strategy (masculine generic, gender-inclusive, and machine translation) on the speed, performance, and perceptions of quadball referee test takers in German. It shows promise for inclusive over masculine strategies, and suggests limited usefulness of MT in this context
Ontwikkelingen rond literair vertalen en technologie : een inleiding
No full textIn deze inleiding op het dossier ‘Literaire vertaling en technologie’ kijken we eerst naar de geschiedenis van de vertaaltechnologie. Vervolgens reflecteren we kort op de verhouding tussen technologie en literair vertalen in en buiten de vertaalwetenschap. Met deze introductie leggen we uit waarom dit dossier juist nu verschijnt. Bij wijze van conclusie gaan we ook nog even in op de dossierbijdragen
How adaptive is adaptive machine translation, really? A gender-neutral language use case
No full textThis study examines the effectiveness of
adaptive machine translation (AMT) for
gender-neutral language (GNL) use in
English-German translation using the
ModernMT engine. It investigates gender bias
in initial output and adaptability to two distinct
GNL strategies, as well as the influence of
translation memory (TM) use on adaptivity.
Findings indicate that despite inherent gender
bias, machine translation (MT) systems show
potential for adapting to GNL with appropriate
exposure and training, highlighting the
importance of customisation, exposure to
diverse examples, and better representation of
different forms for enhancing gender-fair
translation strategies
You shall know a word’s gender by the company it keeps : comparing the role of context in human gender assumptions with MT
No full textIn this paper, we analyse to what extent machine translation (MT) systems and humans base their gender translations and associations on role names and on stereotypicality in the absence of (generic) grammatical gender cues in language. We compare an MT system’s choice of gender for a certain word when translating from a notional gender language, English, into a grammatical gender language, German, with the gender associations of humans. We outline a comparative case study of gender translation and annotation of words in isolation, out-of-context, and words in sentence contexts. The analysis reveals patterns of gender (bias) by MT and gender associations by humans for certain (1) out-of-context words and (2) words in-context. Our findings reveal the impact of context on gender choice and translation and show that wordlevel analyses fall short in such studies
Proceedings of the 3rd Workshop on Gender-Inclusive Translation Technologies (GITT 2025)
No full textDeBiasByUs : raising awareness and creating a database of MT bias
No full textThis 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
Proceedings of the 2nd International Workshop on Gender-Inclusive Translation Technologies
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