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Uncertainty of Vowel Predictions as a Digital Biomarker for Ataxic Dysarthria.

Publication ,  Journal Article
Isaev, DY; Vlasova, RM; Di Martino, JM; Stephen, CD; Schmahmann, JD; Sapiro, G; Gupta, AS
Published in: Cerebellum (London, England)
April 2024

Dysarthria is a common manifestation across cerebellar ataxias leading to impairments in communication, reduced social connections, and decreased quality of life. While dysarthria symptoms may be present in other neurological conditions, ataxic dysarthria is a perceptually distinct motor speech disorder, with the most prominent characteristics being articulation and prosody abnormalities along with distorted vowels. We hypothesized that uncertainty of vowel predictions by an automatic speech recognition system can capture speech changes present in cerebellar ataxia. Speech of participants with ataxia (N=61) and healthy controls (N=25) was recorded during the "picture description" task. Additionally, participants' dysarthric speech and ataxia severity were assessed on a Brief Ataxia Rating Scale (BARS). Eight participants with ataxia had speech and BARS data at two timepoints. A neural network trained for phoneme prediction was applied to speech recordings. Average entropy of vowel tokens predictions (AVE) was computed for each participant's recording, together with mean pitch and intensity standard deviations (MPSD and MISD) in the vowel segments. AVE and MISD demonstrated associations with BARS speech score (Spearman's rho=0.45 and 0.51), and AVE demonstrated associations with BARS total (rho=0.39). In the longitudinal cohort, Wilcoxon pairwise signed rank test demonstrated an increase in BARS total and AVE, while BARS speech and acoustic measures did not significantly increase. Relationship of AVE to both BARS speech and BARS total, as well as the ability to capture disease progression even in absence of measured speech decline, indicates the potential of AVE as a digital biomarker for cerebellar ataxia.

Duke Scholars

Published In

Cerebellum (London, England)

DOI

EISSN

1473-4230

ISSN

1473-4222

Publication Date

April 2024

Volume

23

Issue

2

Start / End Page

459 / 470

Related Subject Headings

  • Uncertainty
  • Quality of Life
  • Neurology & Neurosurgery
  • Humans
  • Dysarthria
  • Cerebellar Ataxia
  • Biomarkers
  • Ataxia
  • 5204 Cognitive and computational psychology
  • 5202 Biological psychology
 

Citation

APA
Chicago
ICMJE
MLA
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Isaev, D. Y., Vlasova, R. M., Di Martino, J. M., Stephen, C. D., Schmahmann, J. D., Sapiro, G., & Gupta, A. S. (2024). Uncertainty of Vowel Predictions as a Digital Biomarker for Ataxic Dysarthria. Cerebellum (London, England), 23(2), 459–470. https://doi.org/10.1007/s12311-023-01539-z
Isaev, Dmitry Yu, Roza M. Vlasova, J Matias Di Martino, Christopher D. Stephen, Jeremy D. Schmahmann, Guillermo Sapiro, and Anoopum S. Gupta. “Uncertainty of Vowel Predictions as a Digital Biomarker for Ataxic Dysarthria.Cerebellum (London, England) 23, no. 2 (April 2024): 459–70. https://doi.org/10.1007/s12311-023-01539-z.
Isaev DY, Vlasova RM, Di Martino JM, Stephen CD, Schmahmann JD, Sapiro G, et al. Uncertainty of Vowel Predictions as a Digital Biomarker for Ataxic Dysarthria. Cerebellum (London, England). 2024 Apr;23(2):459–70.
Isaev, Dmitry Yu, et al. “Uncertainty of Vowel Predictions as a Digital Biomarker for Ataxic Dysarthria.Cerebellum (London, England), vol. 23, no. 2, Apr. 2024, pp. 459–70. Epmc, doi:10.1007/s12311-023-01539-z.
Isaev DY, Vlasova RM, Di Martino JM, Stephen CD, Schmahmann JD, Sapiro G, Gupta AS. Uncertainty of Vowel Predictions as a Digital Biomarker for Ataxic Dysarthria. Cerebellum (London, England). 2024 Apr;23(2):459–470.
Journal cover image

Published In

Cerebellum (London, England)

DOI

EISSN

1473-4230

ISSN

1473-4222

Publication Date

April 2024

Volume

23

Issue

2

Start / End Page

459 / 470

Related Subject Headings

  • Uncertainty
  • Quality of Life
  • Neurology & Neurosurgery
  • Humans
  • Dysarthria
  • Cerebellar Ataxia
  • Biomarkers
  • Ataxia
  • 5204 Cognitive and computational psychology
  • 5202 Biological psychology