Abstract
Gender-inclusive machine translation (MT) should preserve gender ambiguity in the source to avoid misgendering and representational harms. While gender ambiguity often occurs naturally in notional gender languages such as English, maintaining that gender neutrality in grammatical gender languages is a challenge. Here we assess the sensitivity of 21 MT systems to the need for gender neutrality in response to gender ambiguity in three translation directions of varying difficulty. The specific gender-neutral strategies that are observed in practice are categorized and discussed. Additionally, we examine the effect of binary gender stereotypes on the use of gender-neutral translation. In general, we report a disappointing absence of gender-neutral translations in response to gender ambiguity. However, we observe a small handful of MT systems that switch to gender neutral translation using specific strategies, depending on the target language.
Abstract (translated)
性别包容性机器翻译（MT）应当保留源语言中的性别含糊性，以避免错误指代和代表性伤害。虽然英语等概念性别语言中常常自然存在性别模糊性，在具有语法性别语言中保持这种性别中立是一个挑战。在这里，我们评估了21种机器翻译系统在三种不同难度的翻译方向上对性别中立需求的敏感度。实践中观察到的具体性别中立策略被分类和讨论。此外，我们还考察了二元性别刻板印象对使用性别中立翻译的影响。总体而言，我们报告说，在应对性别模糊性时，缺乏性别中立翻译的情况令人失望。然而，我们也注意到一小部分机器翻译系统在面对特定目标语言时会采用具体策略转向性别中立的翻译。
URL
https://arxiv.org/abs/2506.15676
