# Gender Aware Spoken Language Translation Applied to English-Arabic

arXiv: https://arxiv.org/abs/1802.09287 · HTML: https://mlsanity.com/paper/1802.09287/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Feb 2018.

## Built on by (most cited first, 18 of 18)

- [Societal Biases in Language Generation: Progress and Challenges](https://mlsanity.com/paper/2105.04054/) (2021)
- [Gender Bias in Machine Translation](https://mlsanity.com/paper/2104.06001/) (2021)
- [A Survey on Gender Bias in Natural Language Processing](https://mlsanity.com/paper/2112.14168/) (2021)
- [ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages](https://mlsanity.com/paper/2305.10510/) (2023)
- [CoCoA-MT: A Dataset and Benchmark for Contrastive Controlled MT with Application to Formality](https://mlsanity.com/paper/2205.04022/) (2022)
- [Examining Covert Gender Bias: A Case Study in Turkish and English Machine Translation Models](https://mlsanity.com/paper/2108.10379/) (2021)
- [The Arabic Parallel Gender Corpus 2.0: Extensions and Analyses](https://mlsanity.com/paper/2110.09216/) (2021)
- [Multi-Domain Adaptation in Neural Machine Translation Through Multidimensional Tagging](https://mlsanity.com/paper/2102.10160/) (2021)
- [Logic Against Bias: Textual Entailment Mitigates Stereotypical Sentence Reasoning](https://mlsanity.com/paper/2303.05670/) (2023)
- [Improving Gender Translation Accuracy with Filtered Self-Training](https://mlsanity.com/paper/2104.07695/) (2021)
- [Voice, Bias, and Coreference: An Interpretability Study of Gender in Speech Translation](https://mlsanity.com/paper/2511.21517/) (2025)
- [Towards Personalised and Document-level Machine Translation of Dialogue](https://mlsanity.com/paper/2102.10979/) (2021)
- [Controlling Extra-Textual Attributes about Dialogue Participants -- A Case Study of English-to-Polish Neural Machine Translation](https://mlsanity.com/paper/2205.04747/) (2022)
- [Gender Bias in English-to-Greek Machine Translation](https://mlsanity.com/paper/2506.09558/) (2025)
- [The User-Aware Arabic Gender Rewriter](https://mlsanity.com/paper/2210.07538/) (2022)
- [Current State-of-the-Art of Bias Detection and Mitigation in Machine Translation for African and European Languages: a Review](https://mlsanity.com/paper/2410.21126/) (2024)
- [Alexandria: A Multi-Domain Dialectal Arabic Machine Translation Dataset for Culturally Inclusive and Linguistically Diverse LLMs](https://mlsanity.com/paper/2601.13099/) (2026)
- [ConGA: Guidelines for Contextual Gender Annotation. A Framework for Annotating Gender in Machine Translation](https://mlsanity.com/paper/2603.17962/) (2026)

## Abstract (arXiv)

Spoken Language Translation (SLT) is becoming more widely used and becoming a communication tool that helps in crossing language barriers. One of the challenges of SLT is the translation from a language without gender agreement to a language with gender agreement such as English to Arabic. In this paper, we introduce an approach to tackle such limitation by enabling a Neural Machine Translation system to produce gender-aware translation. We show that NMT system can model the speaker/listener gender information to produce gender-aware translation. We propose a method to generate data used in adapting a NMT system to produce gender-aware. The proposed approach can achieve significant improvement of the translation quality by 2 BLEU points.