Self-supervised speech encoders show speaker-group bias from the first latent layers, with SID bias lowest where overall error is lowest while ASR bias is highest where overall error is lowest; the ASR pattern persists after fine-tuning.
Gender Representa- tion in French Broadcast Corpora and Its Impact on ASR Perfor- mance,
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Where Do Self-Supervised Speech Models Become Unfair?
Self-supervised speech encoders show speaker-group bias from the first latent layers, with SID bias lowest where overall error is lowest while ASR bias is highest where overall error is lowest; the ASR pattern persists after fine-tuning.