Progress in dialectal speech technology is hindered by the scarcity of large-scale, real-world corpora. For Minnan speech, existing resources remain limited, and few provide paired Minnan and Mandarin transcripts at scale. To address these gaps, we introduce WenetSpeech-Min, an open-source corpus comprising around 10,0...
Hao-Yu Zhang, Chun-Jiang He, Hong-Tao Li et al.· 0 citations
Conversational context provides semantic and acoustic cues across turns for automatic speech recognition (ASR), but relying on historical transcripts can propagate recognition errors and discard pronunciation and speaker information. We present a multimodal conversational-context framework for LLM-based ASR that integr...
Long-Hao Li, Jian Tang, Yu-Xiang Kong et al.· 0 citations
In recent years, automatic speech recognition (ASR) has witnessed transformative advancements driven by three complementary paradigms: data scaling, model scaling, and deep integration with large language models (LLMs). However, bridging the gap between academic benchmark performance and real-world production utility r...
Chuan-Meng Bian, Da-Ren Chen, Pei-Xin Chen et al.· 2 citations
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