Automated Vowel Articulation Analysis in Connected Speech Among Progressive Neurological Diseases, Dysarthria Types, and Dysarthria Severities.
Purpose: Although articulatory impairment represents distinct speech characteristics in most neurological diseases affecting movement, methods allowing automated assessments of articulation deficits from the connected speech are scarce. This study aimed to design a fully automated method for analyzi...
| Publicado en: | Journal of Speech, Language & Hearing Research Vol. 66; no. 8; pp. 2600 - 2622 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
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American Speech-Language-Hearing Association
Aug2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=169774223&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 169774223 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 10924388 1SM jtl: Journal of Speech, Language & Hearing Research issn: 10924388 maglogo: N pubinfo: dt: Aug2023 vid: 66 iid: 8 pid: 42 pub: American Speech-Language-Hearing Association artinfo: ui: 169774223 10.1044/2023_JSLHR-22-00526 ppf: 2600 ppct: 22 formats: fmt: @attributes: type: P size: 2.5MB tig: atl: Automated Vowel Articulation Analysis in Connected Speech Among Progressive Neurological Diseases, Dysarthria Types, and Dysarthria Severities. aug: au: Illner, Vojtech Tykalova, Tereza Skrabal, Dominik Klempir, Jiri Rusz, Jan affil: Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Czech Republic. Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic. Department of Neurology and ARTORG Center, Inselspital, Bern University Hospital, University of Bern, Switzerland. su: Speech disorders Quantitative research Disease risk factors Vowels Statistics Dysarthria Neurological disorders Fisher exact test Severity of illness index Automation Research funding Descriptive statistics Sensitivity & specificity (Statistics) Data analysis software Data analysis Algorithms Disease complications sug: subj: Speech disorders Quantitative research Disease risk factors Vowels Statistics Dysarthria Neurological disorders Fisher exact test Severity of illness index Automation Research funding Descriptive statistics Sensitivity & specificity (Statistics) Data analysis software Data analysis Algorithms Disease complications ab: Purpose: Although articulatory impairment represents distinct speech characteristics in most neurological diseases affecting movement, methods allowing automated assessments of articulation deficits from the connected speech are scarce. This study aimed to design a fully automated method for analyzing dysarthria-related vowel articulation impairment and estimate its sensitivity in a broad range of neurological diseases and various types and severities of dysarthria. Method: Unconstrained monologue and reading passages were acquired from 459 speakers, including 306 healthy controls and 153 neurological patients. The algorithm utilized a formant tracker in combination with a phoneme recognizer and subsequent signal processing analysis. Results: Articulatory undershoot of vowels was presented in a broad spectrum of progressive neurodegenerative diseases, including Parkinson's disease, progressive supranuclear palsy, multiple-system atrophy, Huntington's disease, essential tremor, cerebellar ataxia, multiple sclerosis, and amyotrophic lateral sclerosis, as well as in related dysarthria subtypes including hypokinetic, hyperkinetic, ataxic, spastic, flaccid, and their mixed variants. Formant ratios showed a higher sensitivity to vowel deficits than vowel space area. First formants of corner vowels were significantly lower for multiple-system atrophy than cerebellar ataxia. Second formants of vowels /a/ and /i/ were lower in ataxic compared to spastic dysarthria. Discriminant analysis showed a classification score of up to 41.0% for disease type, 39.3% for dysarthria type, and 49.2% for dysarthria severity. Algorithm accuracy reached an F-score of 0.77. Conclusions: Distinctive vowel articulation alterations reflect underlying pathophysiology in neurological diseases. Objective acoustic analysis of vowel articulation has the potential to provide a universal method to screen motor speech disorders. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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