STTR Phase I: The SonoVoice Voice Evaluation and Monitoring System

Award ID: 2416498

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project lies in its potential to improve the diagnosis and treatment of voice disorders. Voice disorders affect an estimated one in eight adults in the United States annually, costing nearly $15 billion in healthcare expenses. This proposal focuses on a portable digital device and smartphone application for voice health evaluations to potentially enhance our understanding of vocal health. The potential societal impact of the innovation could be to improve the quality of life for millions of individuals with voice disorders. The commercial potential of the system derives from its potential large user base: it is designed to meet the needs of both voice-specialized clinicians and the primary care workforce, addressing a substantial market opportunity. The proposed technology employs a unique combination of modern digital electronics and machine learning that provides a durable competitive advantage centered on affordability, portability and precision. This Small Business Technology Transfer (STTR) Phase I project proposes to develop a novel system for voice health evaluation. The problem being addressed is the current lack of accessible, precise, and affordable tools for diagnosing voice disorders. The research objectives are to conduct iterative prototyping and calibration of a digital device and smartphone application, followed by their rigorous validation with human subjects to ensure accuracy and reliability in voice health evaluations. The proposed research will involve initial concept design, feasibility testing, iterative prototyping, calibration, and extensive validation with human subjects to ensure the precision, reliability, and user-friendliness of the multimodal voice assessment tool. The anticipated technical result is the successful development of an affordable, reliable, and easy-to-use device for voice health evaluation that captures and classifies differential vocal performance over a range of vocal tract resistances, thereby providing a comprehensive picture of vocal function. This project's intellectual merit lies in its potential to advance knowledge in the field of vocal health assessment, providing a solution that is not only technologically advanced but also broadly accessible. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Alastair Monk