How to Split: the Effect of Word Segmentation on Gender Bias in Speech Translation

Understand

Having recognized gender bias as a major issue affecting current translation technologies, researchers have primarily attempted to mitigate it by working on the data front.

• However, whether algorithmic aspects concur to exacerbate unwanted outputs remains so far under-investigated.
• In this work, we bring the analysis on gender bias in automatic translation onto a seemingly neutral yet critical component: word segmentation.
• Can segmenting methods influence the ability to translate gender? Do certain segmentation approaches penalize the representation of feminine linguistic markings? We address these questions by comparing 5 existing segmentation strategies on the target side of speech translation systems.