VOICE PATHOLOGY DETECTION AND CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORKS
Yeddula Harshitha1, K. Hari Krishna2, Department of Pharmacology, Pulla Reddy College of Pharmacy, Hyderabad
DOI : https://doi.org/10.63712/bpsrj-v1i3p005
ABSTRACT:
Recent advancements in machine learning and digital signal processing have enabled innovative approaches for non-invasive medical diagnosis. This study introduces a Human Sound-based Disease Detecting System (HSDDS), which utilizes Convolutional Neural Networks (CNNs) to analyze human audio signals for early detection of health abnormalities. Human sounds, such as breathing, coughing, and vocal patterns, exhibit acoustic variations that can serve as indicators of underlying medical conditions.