Unveiling 30 years of research on speech biomarker of dementia using text mining

As the incidence and prevalence of dementia continue to rise, there is a critical need for more cost- and time-efficient diagnostic tools. Analysis of speech prosody has emerged as a promising noninvasive biomarker, potentially offering a more accessible approach to dementia identification. However, the absence of a longitudinal analysis of thematic evolution within the extensive literature in this domain has resulted in a notable knowledge gap.

We conducted a text mining analysis of publications from the past 30 years to identify key research trends, thematic patterns, and associated topics.

Our analysis yielded three major findings: a marked acceleration in research activity since 2020, a convergence of clinical needs with technological advancements, and the inherently interdisciplinary nature of this field.

These findings not only underscore the dynamic evolution of dementia research but also highlight the potential of speech prosody analysis as a viable, noninvasive diagnostic tool. Future research integrating multidisciplinary approaches and evaluating diagnostic values of speech prosody is warranted.