FairASR pretrains a Conformer with InfoNCE plus a gradient-reversed supervised contrastive loss over demographic labels, reducing demographic WER gaps on FairSpeech with small overall WER cost.
Unlike most prior work that ad- dresses fairness post hoc, FairASR directly encourages demo- graphic invariance during pretraining
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.AS 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
FairASR: Fair Audio Contrastive Learning for Automatic Speech Recognition
FairASR pretrains a Conformer with InfoNCE plus a gradient-reversed supervised contrastive loss over demographic labels, reducing demographic WER gaps on FairSpeech with small overall WER cost.