TEQST

Personalized fine-tuning of Whisper achieves 9.7% WER on dysarthric speech

Researchers adapted Whisper to a single dysarthric speaker using up to 100.8 hours of read speech and user corrections collected via a mobile app, reducing word error rate from a high baseline to 9.7%. Fine-tuning outperformed LoRA adaptation and the Qwen3-ASR foundation model in this personalized setting. The study demonstrates that speaker-specific fine-tuning of foundation ASR models can reach practical deployment quality for dysarthric users.