Speech production integrates respiratory, laryngeal, articulatory, prosodic, linguistic and executive control, so neurodegeneration can leave measurable acoustic traces before conventional clinical scales change. Two decades of work have identified credible candidate speech and voice biomarkers for amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD), yet the field remains fragmented into small, single-condition, single-language models, many of which do not reproduce when evaluated on speakers entirely unseen during training (all recordings from each participant are confined to one data partition, preventing identity leakage between training and testing). In this Perspective we argue that a testable next step is a clinically grounded voice-biomarker foundation model (a single self-supervised backbone, pretrained on large, diverse, ethically sourced, multi-condition speech and adapted to explicit contexts of use), rather than further bespoke classifiers.
We propose ALS bulbar-progression monitoring as a suitable lead context of use because some speech-derived measures appear more responsive than the coarse ALSFRS-R speech item; one ALS speech-analytics platform has received Breakthrough Device designation, an expedited-review status that is neither marketing authorization nor endpoint qualification. We use PD screening as a test case carrying the field’s central cautionary lessons about data leakage, modest real-world operating points, and the potential value of articulation-rich over phonation-only tasks. We separate established evidence from inference and proposed research, define what would justify the “foundation model” label, specify minimum methodological and governance standards, state the limitations candidly, and outline a prospective-validation and regulatory roadmap.
To our knowledge, no speech- or voice-derived endpoint for ALS or PD was qualified by FDA or EMA as of the time of this publication; the foundation-model case is therefore presented as a research agenda, not an achieved capability. Department of Medicine, Division of Hematology and Medical Oncology, St. Luke’s University Health Network, Bethlehem, PA, USA Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA Department of Neurology, Parkinson’s Disease and Movement Disorders Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Correspondence to Arturo Loaiza-Bonilla.
A.L.-B. reports leadership and equity interests in Massive Bio, Inc. P.A. and N.H. are affiliated with Rivvi AI, Inc., which has commercial interests in voice-biomarker foundation models and conversational elicitation agents. The other authors do not have a competing interest.
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