Abstract

Introduction: The Toolkit to Examine Lifelike Language (TELL) is a web-based application providing speech biomarkers of neurodegeneration. After deployment of TELL v.1.0 in over 20 sites, we now introduce TELL v.2.0. Methods: First, we describe the app’s usability features, including functions for collecting and processing data onsite, offline, and via videoconference. Second, we summarize its clinical survey, tapping on relevant habits (e.g., smoking, sleep) alongside linguistic predictors of performance (language history, use, proficiency, and difficulties). Third, we detail TELL’s speech-based assessments, each combining strategic tasks and features capturing diagnostically relevant domains (motor function, semantic memory, episodic memory, and emotional processing). Fourth, we specify the app’s new data analysis, visualization, and download options. Finally, we list core challenges and opportunities for development. Results: Overall, TELL v.2.0 offers scalable, objective, and multidimensional insights for the field. Conclusion: Through its technical and scientific breakthroughs, this tool can enhance disease detection, phenotyping, and monitoring.