Phoneme embeddings in self-supervised ASR models show both random variance and systematic bias as sources of demographic unfairness, with variance hindering fairness more than bias.
Journal of Speech, Language, and Hearing Research, 63(2):533–551
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Identifying and typifying demographic unfairness in phoneme-level embeddings of self-supervised speech recognition models
Phoneme embeddings in self-supervised ASR models show both random variance and systematic bias as sources of demographic unfairness, with variance hindering fairness more than bias.