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Personalized federated learning can reduce word error rates in dysarthric speech recognition by up to 0.99%, highlighting the potential for tailored ASR solutions.
Achieving up to 27.73% absolute WER reduction without any training or additional data challenges the conventional reliance on fine-tuning for model compression.
