Anne-Catherine Bachoud-Lévi on Speech-Based Monitoring of Huntington's Disease

Can speech reveal the progression of a neurodegenerative disease? In this episode of In Conversation With…, Evgenia Koutsouki, Senior Editor at The Lancet Digital Health, speaks with Professor Anne-Catherine Bachoud-Lévi about her team's latest research on NDSNet, a deep learning model that uses speech recordings to estimate clinical status in people with Huntington's disease. They discuss the growing role of speech-based digital biomarkers in neurology, how AI can help monitor disease progression, and why subtle changes in speech may provide valuable insights into underlying brain changes before they become apparent on conventional clinical assessments. The conversation also explores the challenges of validating AI tools in real-world settings and the future of remote, scalable monitoring for Huntington's disease and other neurodegenerative disorders. Tune in to listen to Professor Bachoud-Lévi’s insights on how speech, digital health technologies, and machine learning are reshaping the way we assess and monitor neurological disease. Click here to read the full article: https://www.thelancet.com/journals/landig/article/PIIS2589-7500(26)00048-8/fulltext