Integration of AI-Powered Speech Analysis Tools in Speech Therapy
Integrating AI-powered tools in diagnostics and treatment of Speech Sound Disorders, improving accessibility and reducing Speech-Language Pathologist workload.
I utilized AI-powered speech analysis tools into speech therapy to enhance the diagnosis of Speech Sound Disorders (SSD). Given the limited access to Speech-Language Pathologists (SLPs) and the large number of people with the need for Speech Therapy in the United States, there is a large caseload for SLP's in America. My work aims to bridge this gap by utilizing AI technologies such as automatic speech recognition and large language models. These tools can streamline diagnostics, create individualized therapy materials, and reduce SLP workloads, thereby addressing burnout and improving accessibility to care. Focusing on preschool-aged children due to its relevance in SSD disorder diagnosis, my approach involves reviewing existing diagnostic tools, collaborating with AI and programming experts, developing a coding framework, and planning for validation and replication of the AI system.
