Fine-tuning MMS-1B with auxiliary LID CTC loss on augmented data gives 86.9% LID accuracy and 15.6% CER on the ML-SUPERB 2.0 development set.
Training strategies with multilingual SFMs Table 1 shows LID and ASR results across SFMs and training strategies on ML-SUPERB 2.0
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Improving Multilingual Speech Models on ML-SUPERB 2.0: Fine-tuning with Data Augmentation and LID-Aware CTC
Fine-tuning MMS-1B with auxiliary LID CTC loss on augmented data gives 86.9% LID accuracy and 15.6% CER on the ML-SUPERB 2.0 development set.