A person's voice can express far more than just what they are saying. Researchers are increasingly discovering that subtle changes in speech, breathing and vocal quality provide valuable clues about a wide range of health conditions, from Parkinson's and Alzheimer's to depression, heart failure and type 2 diabetes. These voice-derived indicators, known as vocal biomarkers, are expected to soon be used for disease diagnosis and monitoring.
Co-author of the study Dr. Yael Bensoussan, associate professor of otolaryngology in the USF Health Morsani College of Medicine
To help unlock this potential, researchers and clinicians from the Department of Precision Health (DoPH) at the and the 色色研究所 Morsani College of Medicine have led a new international effort to establish the first consensus-based framework and definitions for vocal biomarkers.
as part of the VOCAL (Vocal Biomarker Guidelines for Ontology, Classification, Application and Logistics) initiative, the study brings together 24 international experts from Europe and North America to address a key challenge facing voice-based health technologies: the lack of a common scientific language.
As research on vocal biomarkers becomes more popular, the field's rapid growth has led to inconsistent terminology, with concepts such as "voice biomarkers," "speech biomarkers" and "vocal biomarkers" often used interchangeably, despite referring to different physiological and cognitive processes.
To address this challenge, 鈥 a European network coordinated by the Luxembourg Institute of Health, and 鈥 a North American consortium funded by the NIH and co-led by USF researchers 鈥 conducted a rigorous multi-stage consensus process between 2024 and 2025. The result is a structured framework that clearly distinguishes between vocal measures and validated vocal biomarkers and introduces a hierarchical model spanning the different domains involved in voice and speech production.
The framework provides a scientifically grounded vocabulary designed to improve collaboration between clinicians, speech and language specialists, engineers, data scientists, regulators and industry stakeholders. It also aims to support the future development of standards, validation pathways and regulatory guidance for voice-based health technologies.
鈥淰oice has enormous potential as a source of health information, but the field cannot progress efficiently without a common language,鈥 said Dr. Guy Fagherazzi, head of the Department of Precision Health at the LIH and chair of eVoiceNet. 鈥淏y defining what we mean when we talk about voice-based health measures, we are creating the foundations for more robust research, greater transparency and, ultimately, clinically useful technologies that can benefit patients.鈥
, associate professor of Otolaryngology at the and co-head of the Bridge2AI-Voice consortium, said the framework reflects both the promise and complexity of vocal biomarker research.
鈥淥ne of the unique strengths of vocal biomarkers is that they capture information from multiple physiological and cognitive systems simultaneously,鈥 Bensoussan said. 鈥淗owever, this complexity is also what has made the field difficult to define. This work provides a structure that allows researchers to speak the same scientific language while preserving the richness of the signal.鈥
The publication marks the first phase of the broader VOCAL initiative, which aims to establish international guidelines and standards for vocal biomarker research and implementation. The researchers hope that a shared vocabulary will help accelerate the translation of voice-based technologies from the lab to the clinic.