A Benchmark for Early-stage Parkinson's Disease Detection from Speech
This study created a standardized benchmark for detecting early-stage Parkinson's disease (EarlyPD) using speech. It addresses inconsistencies in prior research by defining clear criteria for EarlyPD and using speaker-independent splits on open datasets. The benchmark compares three existing speech detection models across different training data settings, showing that increasing speaker diversity improves performance.