Researchers have introduced an AI-powered diagnostic tool using convolutional neural networks (CNNs) with Mel-spectrogram audio analysis to automatically assess the severity of unilateral vocal cord paralysis (UVCP). The TripleConvNet architecture analyzes voice recordings from over 400 subjects, identifying subtle variations linked to vocal fold compensation status. This non-invasive, precise method aims to standardize diagnosis, reduce clinician bias, and facilitate personalized treatment planning in otolaryngology.