Credit: Klick Applied Sciences
Using only smartphone recordings of short English sentences and participant sex as study criteria, scientists at Klick Labs have created visual maps of sound frequencies (spectrograms) to identify complex, new patterns associated with Type 2 diabetes.
In the study, published in theIEEE Journal of Biomedical and Health Informatics, researchers analyzed 14,759 voice recordings from 461 adults, which were converted into a visual spectrogram before being analyzed by an Audio Spectrogram Transformer. The process allows the model to learn complex combinations of acoustic patterns directly from the recordings rather than relying primarily on predefined voice features selected in advance.
Using voice only, the sex-stratified models achieved a balanced accuracy of 71.3 percent for women and 72.4 percent for men, with area under the receiver operating characteristic curve (AUC) values of 0.788 (78.8 percent) and 0.779 (77.9 percent), respectively.
“Now, we can literally see many more clues related to diabetes within vocal biomarkers,” said Yan Fossat, Senior Vice President, Digital Health R&D at Klick Applied Sciences and principal investigator of the study. “By capturing relationships across frequencies and time, we expanded our analysis beyond shimmer, jitter, and other predefined voice features and found complex combinations of acoustic patterns and features that weren’t on anyone’s radar.”
The research builds on Klick Labs’ 2023 Voice to Diabetes study inMayo Clinic Proceedings: Digital Health, which analyzed fixed one-sentence smartphone voice recordings alongside participants’ age, body mass index (BMI), and other basic health information. The study identified 14 predefined acoustic features, including pitch, intensity, shimmer, and jitter, associated with Type 2 diabetes.
In June 2026, Klick Labs announced it has embarked on a series of studies with Mayo Clinic in Florida, exploring the use of novel vocal biomarkers in connection with a number of chronic diseases and serious health conditions.
Data from Klick Applied Sciences