By 2050, more than 150 million people will suffer from a neurodegenerative disorder, such as Alzheimer’s disease, Parkinson’s disease or frontotemporal dementia. This motivates the search for objective, affordable and scalable markers to improve early detection and monitoring of symptoms. Among these efforts, automated speech and language analysis (AAHL) stands out. In fact, multiple investigations support its potential to improve current evaluation procedures. Now, how to convert scientific results into clinical resources? How to go from paper to practical tools? From these questions emerged Toolkit to Examine Lifelike Language (TELL), an app to evaluate speech at the service of brain health.
Every neurodegenerative disorder impacts, in one way or another, various aspects of speech and language. Therefore, the AAHL reveals clinically useful patterns. To do this, it is enough to record the participants’ speech and extract acoustic and linguistic characteristics from the audios and their transcriptions, respectively. Multiple studies indicate that AAHL can identify and differentiate people with Alzheimer’s disease, Parkinson’s disease, and frontotemporal dementia in early stages; discriminate between subtypes of these disorders; and predict the severity and progression of your symptoms. However, the potential of AAHL is limited by several factors, as research protocols are highly heterogeneous, centralized systems for harmonized data management are lacking, and the underlying technologies are not available for clinical use.
TELL is a strategic effort to address such challenges. This web application offers an intuitive platform to collect, encrypt, analyze, download and visualize speech and language data for clinical and research purposes. The application includes a linguistic profile questionnaire and a general protocol with various tasks, which include routine description, video narration and text reading, among others. Each task involves different motor and cognitive demands. State-of-the-art algorithms are used to capture sensitive acoustic measures (such as speech rate, duration of silences, and tonal patterns), as well as word frequency, affective valence, and emotional magnitude. These tasks and metrics have been widely validated through interdisciplinary studies, including work on underrepresented populations such as Latinos. Audio data and automated transcripts are automatically analyzed and graphed for clinical use, and can be downloaded for offline analysis. Likewise, TELL complies with current regulations on the protection of confidential information. The app is free to use for research purposes.
Die App wächst in Umfang und Potenzial. Derzeit wird es in zehn Zentren in sechs verschiedenen Ländern eingesetzt, Tendenz steigend. Aufgaben und Metriken sind in Englisch, Spanisch und Portugiesisch verfügbar, und je nach den spezifischen Anforderungen jedes Projekts werden neue Sprachen hinzugefügt. Im Januar 2023 wurde eine Investition von 500.000 US-Dollar (von SF500, einem argentinischen Biowissenschaftsfonds) für die Entwicklung seiner Version 2.0 gesichert, die neue Metriken und zusätzliche Funktionen enthalten wird. Zusammenfassend ist TELL mit seinen aktuellen und zukünftigen Merkmalen eine vielversprechende Initiative zur Förderung der Gerechtigkeit im globalen Kampf gegen neurodegenerative Erkrankungen.
Um Zugang anzufordern und Einzelheiten, Neuigkeiten und Veröffentlichungen zu erfahren, besuchen Sie die TELL-Website unter https://tellapp.org/ .
