Abstract
Parkinson's Disorder (PD) is a progressive neurodegenerative disorder, which is incurable. Diagnosis of PD at an early stage aids in the delay of the progression. It requires an accurate and robust system to provide early diagnosis of PD. Machine Learning (ML) based techniques help in developing of PD diagnosis system. This study presents a complete review of the various machine learning techniques along with their working principle that helps for the development of PD diagnosis system. This research highlights the summary of methodologies and also presents a generic framework for the PD diagnosis based on voice signals.