Guess What We Can Hear – Novel Voice Biomarkers for the Remote Detection of Disease

ABSTRACT

The advancement of digital biomarkers and the provision of remote healthcare has greatly progressed during the coronavirus-19 global pandemic. Combining voice/speech data with artificial intelligence and machine-based learning offers a novel solution to the growing demand for telemedicine. Voice biomarkers, obtained from the extraction of characteristic acoustic and linguistic features, are associated with a variety of diseases and even coronavirus disease-2019. In the current review we i) describe the basis upon which digital voice biomarkers could facilitate "telemedicine,” ii) discuss potential mechanisms that may explain the association between voice biomarkers and disease, iii) offer a novel classification system to conceptualize voice biomarkers depending upon different methods for recording and analyzing voice/speech samples, iv) outline evidence demonstrating an association between voice biomarkers and a number of disease states, and v) describe the process of developing a voice biomarker from recording and storing voice samples and extracting relevant acoustic and linguistic features to training and testing deep and machine based learning algorithms to detect disease. We further explore several important future considerations in this area of research, including the necessity for clinical trials and importance of safeguarding data and individual privacy. To this end, we searched Pubmed and Google Scholar to identify studies evaluating the relationship between voice/speech features and biomarkers and various diseases. Search terms included "digital biomarker,” "telemedicine,” "voice features,” "voice biomarker,” "speech features,” "speech biomarkers,” "acoustics,” "linguistics,” "cardiovascular disease,” "neurologic disease,” "psychiatric disease,” and "infectious disease.” The search was limited to studies published in English in peer-reviewed journals between 1980 and the present day. To identify potential studies not captured by our database search strategy, we also searched studies listed in the bibliography of relevant publications and reviews.