Language-Independent Acoustic Biomarkers for Quantifying Speech Impairment in Huntington's Disease

Changes in voice and speech are characteristic symptoms of Huntington's disease (HD). Objective methods for quantifying speech impairment that can be used across languages could facilitate assessment of disease progression and intervention strategies. The aim of this study was to analyze acoust...

Full description

Saved in:
Bibliographic Details
Published inAmerican journal of speech-language pathology Vol. 33; no. 3; pp. 1390 - 1405
Main Authors Fahed, Vitória S, Doheny, Emer P, Collazo, Carla, Krzysztofik, Joanna, Mann, Elliot, Morgan-Jones, Philippa, Mills, Laura, Drew, Cheney, Rosser, Anne E, Cousins, Rebecca, Witkowski, Grzegorz, Cubo, Esther, Busse, Monica, Lowery, Madeleine M
Format Journal Article
LanguageEnglish
Published United States 01.05.2024
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Changes in voice and speech are characteristic symptoms of Huntington's disease (HD). Objective methods for quantifying speech impairment that can be used across languages could facilitate assessment of disease progression and intervention strategies. The aim of this study was to analyze acoustic features to identify language-independent features that could be used to quantify speech dysfunction in English-, Spanish-, and Polish-speaking participants with HD. Ninety participants with HD and 83 control participants performed sustained vowel, syllable repetition, and reading passage tasks recorded with previously validated methods using mobile devices. Language-independent features that differed between HD and controls were identified. Principal component analysis (PCA) and unsupervised clustering were applied to the language-independent features of the HD data set to identify subgroups within the HD data. Forty-six language-independent acoustic features that were significantly different between control participants and participants with HD were identified. Following dimensionality reduction using PCA, four speech clusters were identified in the HD data set. Unified Huntington's Disease Rating Scale (UHDRS) total motor score, total functional capacity, and composite UHDRS were significantly different for pairwise comparisons of subgroups. The percentage of HD participants with higher dysarthria score and disease stage also increased across clusters. The results support the application of acoustic features to objectively quantify speech impairment and disease severity in HD in multilanguage studies. https://doi.org/10.23641/asha.25447171.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1058-0360
1558-9110
DOI:10.1044/2024_AJSLP-23-00175