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.
CITATION STYLE
DiChristofano, A., Shuster, H., Chandra, S., & Patwari, N. (2023). Performance Disparities between Accents in Automatic Speech Recognition. In Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023 (Vol. 37, pp. 16200–16201). AAAI Press.
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