AAAI 2023technical20 citations
Performance Disparities between Accents in Automatic Speech Recognition (Student Abstract)
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.
BibTeX
@article{DiChristofano_Shuster_Chandra_Patwari_2024, title={Performance Disparities between Accents in Automatic Speech Recognition (Student Abstract)}, volume={37}, url={https://ojs.aaai.org/index.php/AAAI/article/view/26960}, DOI={10.1609/aaai.v37i13.26960}, abstractNote={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.}, number={13}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={DiChristofano, Alex and Shuster, Henry and Chandra, Shefali and Patwari, Neal}, year={2024}, month={Jul.}, pages={16200-16201} }