Pre-trained ECAPA-TDNN with margin losses reaches 85.95% macro and 90.96% micro accuracy on language identification plus 17.08% EER on verification, beating the official baseline by 45.7%, 15.2%, and 50.8% respectively.
Experimental Details We only participate in the closed-condition track of the Tidy- Lang Challenge 2026, where the model is trained using only the provided Tidy-X dataset
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Spoken Language Identification with Pre-trained Models and Margin Loss
Pre-trained ECAPA-TDNN with margin losses reaches 85.95% macro and 90.96% micro accuracy on language identification plus 17.08% EER on verification, beating the official baseline by 45.7%, 15.2%, and 50.8% respectively.