Combining consistency regularization, R-drop, and the MT loss weight into a single scalar 'total regularization' predicts speech translation quality, and tuning near its optimum yields near-SOTA BLEU on MuST-C.
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Optimal Multi-Task Learning at Regularization Horizon for Speech Translation Task
Combining consistency regularization, R-drop, and the MT loss weight into a single scalar 'total regularization' predicts speech translation quality, and tuning near its optimum yields near-SOTA BLEU on MuST-C.