A Mamba-based state-space ASR model and four fine-tuned self-supervised models achieve claimed state-of-the-art word error rates on whispered and normal speech across three English dialects, including near-perfect results on wTIMIT and CHAINS.
The primary distinction lies in how they are produced
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State-Space Models in Efficient Whispered and Multi-dialect Speech Recognition
A Mamba-based state-space ASR model and four fine-tuned self-supervised models achieve claimed state-of-the-art word error rates on whispered and normal speech across three English dialects, including near-perfect results on wTIMIT and CHAINS.