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Gender Aware Spoken Language Translation Applied to English-Arabic

arXiv 1802.09287 ↗First posted 26 Feb 2018cs.CLcited by 18

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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.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Feb 2018.

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Citing papers per year: 2021: 8; 2022: 3; 2023: 2; 2024: 1; 2025: 2; 2026: 2.

18 papers.

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  1. 2021Societal Biases in Language Generation: Progress and Challengescited by 201
  2. 2021Gender Bias in Machine Translationcited by 116
  3. 2021A Survey on Gender Bias in Natural Language Processingcited by 89
  4. 2023ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languagescited by 33
  5. 2022CoCoA-MT: A Dataset and Benchmark for Contrastive Controlled MT with Application to Formalitycited by 24
  6. 2021Examining Covert Gender Bias: A Case Study in Turkish and English Machine Translation Modelscited by 15
  7. 2021The Arabic Parallel Gender Corpus 2.0: Extensions and Analysescited by 12
  8. 2021Multi-Domain Adaptation in Neural Machine Translation Through Multidimensional Taggingcited by 8
  9. 2023Logic Against Bias: Textual Entailment Mitigates Stereotypical Sentence Reasoningcited by 7
  10. 2021Improving Gender Translation Accuracy with Filtered Self-Trainingcited by 5
  11. 2025Voice, Bias, and Coreference: An Interpretability Study of Gender in Speech Translationcited by 5
  12. 2021Towards Personalised and Document-level Machine Translation of Dialoguecited by 4
6 more
  1. 2022Controlling Extra-Textual Attributes about Dialogue Participants -- A Case Study of English-to-Polish Neural Machine Translationcited by 3
  2. 2025Gender Bias in English-to-Greek Machine Translationcited by 3
  3. 2022The User-Aware Arabic Gender Rewritercited by 1
  4. 2024Current State-of-the-Art of Bias Detection and Mitigation in Machine Translation for African and European Languages: a Reviewcited by 1
  5. 2026Alexandria: A Multi-Domain Dialectal Arabic Machine Translation Dataset for Culturally Inclusive and Linguistically Diverse LLMscited by 1
  6. 2026ConGA: Guidelines for Contextual Gender Annotation. A Framework for Annotating Gender in Machine Translationcited by 0