The User-Aware Arabic Gender Rewriter
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Abstract (arXiv)
We introduce the User-Aware Arabic Gender Rewriter, a user-centric web-based system for Arabic gender rewriting in contexts involving two users. The system takes either Arabic or English sentences as input, and provides users with the ability to specify their desired first and/or second person target genders. The system outputs gender rewritten alternatives of the Arabic input sentences (or their Arabic translations in case of English input) to match the target users' gender preferences.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 32 of its 56 references that are in the map. First posted on arXiv 14 Oct 2022.
Builds on
32 of 56 references.
References · 32
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- 2019Queens are Powerful too: Mitigating Gender Bias in Dialogue Generationcited by 152
- 2019Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddingscited by 146
20 more
- 2021The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Modelscited by 118
- 2021Gender Bias in Machine Translationcited by 116
- 2019It's All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitutioncited by 102
- 2019Getting Gender Right in Neural Machine Translationcited by 98
- 2019Does Gender Matter? Towards Fairness in Dialogue Systemscited by 89
- 2020Reducing Gender Bias in Neural Machine Translation as a Domain Adaptation Problemcited by 86
- 2019Equalizing Gender Biases in Neural Machine Translation with Word Embeddings Techniquescited by 65
- 2020Gender Bias in Multilingual Embeddings and Cross-Lingual Transfercited by 55
- 2016Personalized Machine Translation: Preserving Original Author Traitscited by 47
- 2021NeuTral Rewriter: A Rule-Based and Neural Approach to Automatic Rewriting into Gender-Neutral Alternativescited by 46
- 2020Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learningcited by 44
- 2021They, Them, Theirs: Rewriting with Gender-Neutral Englishcited by 44
- 2020Mitigating Gender Bias in Machine Translation with Target Gender Annotationscited by 42
- 2020Neural Machine Translation Doesn't Translate Gender Coreference Right Unless You Make Itcited by 40
- 2020Automatically Identifying Gender Issues in Machine Translation using Perturbationscited by 28
- 2022Under the Morphosyntactic Lens: A Multifaceted Evaluation of Gender Bias in Speech Translationcited by 23
- 2018Gender Aware Spoken Language Translation Applied to English-Arabiccited by 18
- 2021Examining Covert Gender Bias: A Case Study in Turkish and English Machine Translation Modelscited by 15
- 2021The Arabic Parallel Gender Corpus 2.0: Extensions and Analysescited by 12
- 2022User-Centric Gender Rewritingcited by 7
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