Fusing a wav2vec 2.0 acoustic grader with a task-specific Phi-4 multimodal language model reduces RMSE to 0.375 on the L2 English speaking assessment challenge, ranking second.
BERT: Pre-training of deep bidirectional transformers for language understanding,
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The NTNU System at the S&I Challenge 2025 SLA Open Track
Fusing a wav2vec 2.0 acoustic grader with a task-specific Phi-4 multimodal language model reduces RMSE to 0.375 on the L2 English speaking assessment challenge, ranking second.