By 2050, over 150 million people will be diagnosed neurodegenerative disorders, including Alzheimer’s disease, Parkinson’s disease, and frontotemporal dementia. This scenario has spurred a quest for objective, affordable, scalable markers to improve early detection and symptom monitoring. Prominent among these efforts is automated speech and language analysis (ASLA), with several papers demonstrating its potential to boost current assessment procedures. Yet, how do we translate research findings into clinical resources? How do we move from published results to usable tools? These questions motivated the development of the Toolkit to Examine Lifelike Language (TELL), a novel speech testing app to gain insights on brain health.
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