Measuring Articulatory Patterns in Amyotrophic Lateral Sclerosis Using a Data-Driven Articulatory Consonant Distinctiveness Space Approach.
Purpose: The aim of this study was to leverage data-driven approaches, including a novel articulatory consonant distinctiveness space (ACDS) approach, to better understand speech motor control in amyotrophic lateral sclerosis (ALS). Method: Electromagnetic articulography was used to record tongue an...
| Published in: | Journal of Speech, Language & Hearing Research Vol. 66; pp. 3076 - 3089 |
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| Main Authors: | , , , , , |
| Format: | Article |
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American Speech-Language-Hearing Association
2023 Supplement
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=171330550&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 171330550 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: 2023 Supplement vid: 66 pid: 42 pub: American Speech-Language-Hearing Association artinfo: ui: 171330550 10.1044/2022_JSLHR-22-00320 ppf: 3076 ppct: 13 formats: fmt: @attributes: type: P size: 9MB tig: atl: Measuring Articulatory Patterns in Amyotrophic Lateral Sclerosis Using a Data-Driven Articulatory Consonant Distinctiveness Space Approach. aug: au: Teplansky, Kristin J. Wisler, Alan Green, Jordan R. Heitzman, Daragh Austin, Sara Wang, Jun affil: Department of Speech, Language, and Hearing Sciences, The University of Texas at Austin. Mathematics and Statistics Department, Utah State University, Logan. Department of Communication Sciences and Disorders, MGH Institute of Health Professions, Boston, MA. Speech and Hearing Bioscience and Technology Program, Harvard University, Boston, MA. MDA/ALS Clinic, Texas Neurology, Dallas. Department of Neurology, The University of Texas at Austin. su: Analysis of variance Motor ability Physiological aspects of speech Speech evaluation Machine learning Articulation disorders Electromagnetism Pearson correlation (Statistics) Amyotrophic lateral sclerosis Verbal behavior testing Body movement Consonants Descriptive statistics Articulation (Speech) sug: subj: Analysis of variance Motor ability Physiological aspects of speech Speech evaluation Machine learning Articulation disorders Electromagnetism Pearson correlation (Statistics) Amyotrophic lateral sclerosis Verbal behavior testing Body movement Consonants Descriptive statistics Articulation (Speech) ab: Purpose: The aim of this study was to leverage data-driven approaches, including a novel articulatory consonant distinctiveness space (ACDS) approach, to better understand speech motor control in amyotrophic lateral sclerosis (ALS). Method: Electromagnetic articulography was used to record tongue and lip movement data during the production of 10 consonants from healthy controls (n = 15) and individuals with ALS (n = 47). To assess phoneme distinctness, speech data were analyzed using two classification algorithms, Procrustes matching (PM) and support vector machine (SVM), and the area/volume of the ACDS. Pearson's correlation coefficient was used to examine the relationship between bulbar impairment and the ACDS. Analysis of variance was used to examine the effects of bulbar impairment on consonant distinctiveness and consonant classification accuracies in clinical subgroups. Results: There was a significant relationship between the ACDS and intelligible speaking rate (area, p = .003; volume, p = .010), and the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) bulbar subscore (area, p = .009; volume, p = .027). Consonant classification performance followed a consistent pattern with bulbar severity, where consonants produced by speakers with more severe ALS were classified less accurately (SVM = 75.27%; PM = 74.54%) than the healthy, asymptomatic, and mild-moderate groups. In severe ALS, area of the ACDS was significantly condensed compared to both asymptomatic (p = .004) and mild-moderate (p = .013) groups. There was no statistically significant difference in area between the severe ALS group and healthy speakers (p = .292). Conclusions: Our comprehensive approach is sensitive to early oromotor changes in response due to disease progression. The preserved articulatory consonant space may capture the use of compensatory adaptations to counteract influences of neurodegeneration. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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