The research investigates how GPT-4 alongside other Large Language Models can detect Dysarthria and Apraxia and Stuttering and support their therapy. Rule-based systems together with initial machine learning models proved ineffective at handling the diverse elements of spoken human communication. Deep learning technology and advanced models especially LLMs introduce a new method for detecting and treating speech disorders in patients. The broad text training of LLMs enables them to recognize speech patterns which signal disorders to help patients receive custom feedback for better therapeutic outcomes. This research analyzes how well the analytical models detect speech problems along with their real-time capabilities to assist therapy adaptations. LM technology demonstrates superior performance with GPT-4 leading the way among other models in speech recognition tasks to become crucial tools for enhanced care for speech disorder patients. Healthcare practice enhances precision and accessibility of speech disorder treatments when these models integrate into healthcare systems.