ArticleDigital biomarkers
Repeatability of Commonly Used Speech and Language Features for Clinical Applications.
Article in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- Quantifying articulatory impairments in neurodegenerative motor diseases: A scoping review and meta-analysis of interpretable acoustic features.International journal of speech-language pathology · 2023Pooled it
- Acoustic and Perceptual Characteristics of Compressed Dysarthric Speech: Implications for Teleassessment.Journal of speech, language, and hearing research : JSLHR · 2026Article
- An End-to-End Overview of Clinical Speech AI.IEEE transactions on audio, speech, and language processing (2025) · 2026Article
- Collection and Analysis of Repeated Speech Samples: Methodological Framework and Example Protocol.JMIR research protocols · 2025Article
- Speech Acoustic Markers Can Detect Mild Cognitive Impairment in Parkinson's Disease.IEEE journal of selected topics in signal processing · 2025Article
- Automated analysis of spoken language differentiates multiple system atrophy from Parkinson's disease.Journal of neurology · 2025Article
- Articulatory precision from connected speech as a marker of cognitive decline in Alzheimer's disease risk-enriched cohorts.Journal of Alzheimer's disease : JAD · 2025Article
- Cross-device and test-retest reliability of speech acoustic measurements derived from consumer-grade mobile recording devices.Behavior research methods · 2024Article
- Operationalizing Clinical Speech Analytics: Moving From Features to Measures for Real-World Clinical Impact.Journal of speech, language, and hearing research : JSLHR · 2024Article
- Automated speech analytics in ALS: higher sensitivity of digital articulatory precision over the ALSFRS-R.Amyotrophic lateral sclerosis & frontotemporal degeneration · 2024Article
- Variability in Vowel Space in Parkinson's Disease: Associations With Cognitive and Motor Impairment.Journal of speech, language, and hearing research : JSLHR · 2024Article
- The use of digital tools in rare neurological diseases towards a new care model: a narrative review.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024Review
- Responsible development of clinical speech AI: Bridging the gap between clinical research and technology.NPJ digital medicine · 2024Review
- Digital markers of motor speech impairments in spontaneous speech of patients with ALS-FTD spectrum disorders.Amyotrophic lateral sclerosis & frontotemporal degeneration · 2024Article
- Reliability and validity of a widely-available AI tool for assessment of stress based on speech.Scientific reports · 2023Article
- Zero-shot personalization of speech foundation models for depressed mood monitoring.Patterns (New York, N.Y.) · 2023Article
- A speech-based prognostic model for dysarthria progression in ALS.Amyotrophic lateral sclerosis & frontotemporal degeneration · 2023Article
- Language Analytics for Assessment of Mental Health Status and Functional Competency.Schizophrenia bulletin · 2023Article
- Semantic and Acoustic Markers in Schizophrenia-Spectrum Disorders: A Combinatory Machine Learning Approach.Schizophrenia bulletin · 2023Article
- Wearable device and smartphone data quantify ALS progression and may provide novel outcome measures.NPJ digital medicine · 2023Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
Abstract
introductionChanges in speech have the potential to provide important information on the diagnosis and progression of various neurological diseases. Many researchers have relied on open-source speech features to develop algorithms for measuring speech changes in clinical populations as they are convenient and easy to use. However, the repeatability of open-source features in the context of neurological diseases has not been studied.
methodsWe used a longitudinal sample of healthy controls, individuals with amyotrophic lateral sclerosis, and individuals with suspected frontotemporal dementia, and we evaluated the repeatability of acoustic and language features separately on these 3 data sets.
resultsRepeatability was evaluated using intraclass correlation (ICC) and the within-subjects coefficient of variation (WSCV). In 3 sets of tasks, the median ICC were between 0.02 and 0.55, and the median WSCV were between 29 and 79%.
conclusionOur results demonstrate that the repeatability of speech features extracted using open-source tool kits is low. Researchers should exercise caution when developing digital health models with open-source speech features. We provide a detailed summary of feature-by-feature repeatability results (ICC, WSCV, SE of measurement, limits of agreement for WSCV, and minimal detectable change) in the online supplementary material so that researchers may incorporate repeatability information into the models they develop.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.