Joint fine-tuning on seven dysarthric speakers' data reduced per-speaker character error rates by up to 13.15 percentage points compared to single-speaker fine-tuning on the CDSD corpus.
However, the specific nature of this inter-speaker conflict among dysarthric populations remains unclear
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Cross-Learning Fine-Tuning Strategy for Dysarthric Speech Recognition Via CDSD database
Joint fine-tuning on seven dysarthric speakers' data reduced per-speaker character error rates by up to 13.15 percentage points compared to single-speaker fine-tuning on the CDSD corpus.