In this review, we are looking at Parkinson’s Disease, specifically how it impacts on speech and voice functions that include hypokinetic dysarthria which affects both communication and emotional expression. This paper highlights the importance of voice analysis during early stages of PD through a focus on Artificial Intelligence (AI) and Machine Learning (ML) for PD diagnosis. It also examines speech changes in PD, such as diminished pitch variability and lower articulatory precision, and underlies gender specific contrasts. With increased global incidence rates of PD presentation with both motor and non-motor symptoms like sleep issues among others, this study argues for voice changes to be signs of early stage PD. In general, its purpose is to improve diagnostic techniques as well as treatments holistically. One of the main issues addressed in this article is the role played by speech analysis and voices in identifying people who have been affected with Parkinson disease at an early stage; especially when it comes to constant monitoring of symptoms or clinical decision-making based on information provided by smartphones. The recommendations also highlight special therapies for enhancing sociability and psychological well-being among those suffering from PD. Finally, the study suggests further researches and technological improvements concerning symptomatic speeches caused by Parkinson’s disease with an emphasis on making affordable home-based monitoring devices that would be integrated into healthcare facilities.