A three-stage pipeline of mono-accent LoRA experts, hierarchical routing, and phoneme-plus-word LLM error correction cuts accented-English WER from 6.34% to 2.07% on a combined 9-accent test set.
Hybrid CTC/Attention Architecture for End-to- End Speech Recognition,
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Mixture of LoRA Experts with Multi-Modal and Multi-Granularity LLM Generative Error Correction for Accented Speech Recognition
A three-stage pipeline of mono-accent LoRA experts, hierarchical routing, and phoneme-plus-word LLM error correction cuts accented-English WER from 6.34% to 2.07% on a combined 9-accent test set.