AAAI 2023Technical
Performance Disparities between Accents in Automatic Speech Recognition (Student Abstract)
Authors: Alex DiChristofano, Henry Shuster, Shefali Chandra, Neal Patwari
Abstract
In this work, we expand the discussion of bias in Automatic Speech Recognition (ASR) through a large-scale audit. Using a large and global data set of speech, we perform an audit of some of the most popular English ASR services. 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.