SHNU-mASR, a parallel-encoder LLM system, achieves 11.76% CER/WER on the MLC-SLM blind eval set, 8.41 points better than the official baseline.
Multilin- gual ASR (mASR) extends this capability to multiple languages within a single system, enhancing global communication and supporting low-resource languages
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SHNU Multilingual Conversational Speech Recognition System for INTERSPEECH 2025 MLC-SLM Challenge
SHNU-mASR, a parallel-encoder LLM system, achieves 11.76% CER/WER on the MLC-SLM blind eval set, 8.41 points better than the official baseline.