论文标题
在性别语言的单词嵌入中测量性别偏见需要解开语法性别信号
Measuring Gender Bias in Word Embeddings of Gendered Languages Requires Disentangling Grammatical Gender Signals
论文作者
论文摘要
在测量其单词嵌入捕获的语义性别信息时，语言的语法性别会干扰吗？性别语言嵌入中的许多异常性别偏见测量表明这可能性。我们证明，嵌入词在语法性别语言中学习名词与其语法性别之间的关联，这可能会使社会性别偏见的测量差异。因此，引入了单词嵌入后处理方法，以量化，分解和评估语法性别信号。该评估是对印度 - 欧洲语言家族的日耳曼语，浪漫和斯拉夫分支的五种性别语言进行的。我们的方法将语法性别信号的强度降低了，以效应大小（Cohen's D）来衡量，法语，德语和意大利语的平均值为d = 1.3，而波兰语和西班牙语则为0.56。一旦语法性别被解散，10,000个无生命名词中的90％以上的关联及其指定的语法性别削弱，而嵌入式嵌入关联测试（WEAT）一词的跨语言偏见与国家级别的隐式偏见测量结果更加一致。结果进一步表明，从单词嵌入中解开语法性别信号可能会导致语义机学习任务的改善。
Does the grammatical gender of a language interfere when measuring the semantic gender information captured by its word embeddings? A number of anomalous gender bias measurements in the embeddings of gendered languages suggest this possibility. We demonstrate that word embeddings learn the association between a noun and its grammatical gender in grammatically gendered languages, which can skew social gender bias measurements. Consequently, word embedding post-processing methods are introduced to quantify, disentangle, and evaluate grammatical gender signals. The evaluation is performed on five gendered languages from the Germanic, Romance, and Slavic branches of the Indo-European language family. Our method reduces the strength of grammatical gender signals, which is measured in terms of effect size (Cohen's d), by a significant average of d = 1.3 for French, German, and Italian, and d = 0.56 for Polish and Spanish. Once grammatical gender is disentangled, the association between over 90% of 10,000 inanimate nouns and their assigned grammatical gender weakens, and cross-lingual bias results from the Word Embedding Association Test (WEAT) become more congruent with country-level implicit bias measurements. The results further suggest that disentangling grammatical gender signals from word embeddings may lead to improvement in semantic machine learning tasks.
