VocaSense-X Framework: Advancing Voice Medicine Through Intelligent Diagnosis and Rehabilitation.

چکیده اصلی

Voice disorders are a significant clinical issue that affect millions of people worldwide and can impair their quality of life, professional functioning, and communication. Current methods of diagnosis may be based on subjective clinical examination and disjointed rehabilitation regimens, which may lack accuracy and scalability. The study introduces the VocaSense-X Framework, a comprehensive intelligent system for improving voice medicine through integrated diagnosis and rehabilitation. The framework uses multimodal signal processing, deep learning models, and adaptive feedback mechanisms to provide accurate, data-driven analysis of vocal pathologies, including dysphonia, vocal fold lesions, and neurogenic voice disorders. VocaSense-X is a model that combines a real-time acoustic feature extraction pipeline with a hybrid convolutional-recurrent neural network, achieving superior classification performance across a wide range of patient populations. The framework includes a personalized rehabilitation module that dynamically adjusts therapeutic exercises based on continuous monitoring of the voice, enabling tracking of the patient's progress over time and supporting diagnosis. The experimental analysis using benchmark voice disorder datasets demonstrates that the diagnostic performance of VocaSense-X is significantly better than that of any other comparator architecture tested under the same experimental setup, with an accuracy of > 94. Furthermore, clinician usability tests confirm the framework's usability in both clinical and teletherapy settings. The system proposed herein is designed to fill the gap between intelligent computation and clinical voice medicine, is scalable and evidence-based, and can be used for early detection and structured voice rehabilitation. The implications of VocaSense-X for otolaryngology, speech-language pathology, and digital health platforms make it a pivotal step towards AI-driven voice healthcare innovations.

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