论文标题
部分可观测时空混沌系统的无模型预测
Global Performance Disparities Between English-Language Accents in Automatic Speech Recognition
论文作者
论文摘要
过去的研究已将歧视性自动语音识别（ASR）表现确定为演讲者的种族群体和国籍的函数。在本文中，我们将讨论扩展到偏见之外，这是议长的个别民族起源的函数，以寻求偏见作为其原籍国的地缘政治取向的函数。我们使用语音Accent Archive中的大型和全球数据的语音集审核了一些最受欢迎的英语ASR服务，其中包括2700多名英语发言人，出生于171个不同国家 /地区。我们表明，即使控制多种语言协变量，ASR服务绩效与美国人出生国在美国的地缘政治权力方面的政治统一性具有统计学意义的关系。这适用于所有已测试的ASR服务。我们在历史使用语言维持全球和政治权力的背景下讨论了这种偏见。
Past research has identified discriminatory automatic speech recognition (ASR) performance as a function of the racial group and nationality of the speaker. In this paper, we expand the discussion beyond bias as a function of the individual national origin of the speaker to look for bias as a function of the geopolitical orientation of their nation of origin. We audit some of the most popular English language ASR services using a large and global data set of speech from The Speech Accent Archive, which includes over 2,700 speakers of English born in 171 different countries. We show that, even when controlling for multiple linguistic covariates, ASR service performance has a statistically significant relationship to the political alignment of the speaker's birth country with respect to the United States' geopolitical power. This holds for all ASR services tested. We discuss this bias in the context of the historical use of language to maintain global and political power.
