Diving into gender translation bias for the Portuguese language

ACL ARR 2025 February Submission1142 Authors

Abstract: Bias in Machine Translation models has become a significant concern. Despite extensive research in several language pairs, Portuguese remains under-explored. This study investigates gender bias in English-to-Portuguese translation. We conduct several experiments, extending an established dataset, and provide a comparative analysis of commercial Machine Translation systems, general-purpose LLMs, and non-commercial translation-specific models across various dimensions of gender bias. Additionally, we compare gender bias in Portuguese translation with that in other Romance languages (French, Spanish, and Italian). Finally, we explore whether sentiment influences gender bias in English-to-Portuguese translation.

Paper Type: Long

Research Area: Ethics, Bias, and Fairness

Research Area Keywords: Ethics, Bias, and Fairness: model bias/fairness evaluation; Machine Translation: biases; Resources and Evaluation: benchmarking

Contribution Types: Model analysis & interpretability, Data resources

Languages Studied: Portuguese, French, Italian, Spanish

Submission Number: 1142