Articulatory Distinctiveness of Vowels and Consonants: A Data-Driven Approach.
Purpose: To quantify the articulatory distinctiveness of 8 major English vowels and 11 English consonants based on tongue and lip movement time series data using a data-driven approach.Method: Tongue and lip movements of 8 vowels and 11 consonants from 10 healthy talkers were collected. First, class...
| Publicado en: | Journal of Speech, Language & Hearing Research Vol. 56; no. 5; pp. 1539 - 1552 |
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| Autores principales: | , , , |
| Formato: | Artículo |
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American Speech-Language-Hearing Association
Oct2013
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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=91624470&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 91624470 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: Oct2013 vid: 56 iid: 5 pid: 42 pub: American Speech-Language-Hearing Association artinfo: ui: 91624470 10.1044/1092-4388(2013/12-0030) ppf: 1539 ppct: 13 formats: fmt: @attributes: type: P size: 349KB tig: atl: Articulatory Distinctiveness of Vowels and Consonants: A Data-Driven Approach. aug: au: Jung Wang Green, Jordan R. Samal, Ashok Yana Yunusova affil: University of Nebraska-Lincoln Munroe-Meyer Institute, University of Nebraska Medical Center, Omaha Callier Center for Communication Disorders, University of Texas at Dallas MGH Institute of Health Professions, Boston, MA University of Toronto, Toronto, Ontario, Canada su: Midwest (U.S.) Physiology Tongue physiology Lips Consonants Research funding Speech evaluation Physiological aspects of speech Vowels Data analysis software sug: subj: Physiology Midwest (U.S.) Tongue physiology Lips Consonants Research funding Speech evaluation Physiological aspects of speech Vowels Data analysis software keyword: articulatory consonant space articulatory vowel space Procrustes analysis speech production support vector machine articulatory consonant space articulatory vowel space Procrustes analysis speech production support vector machine ab: Purpose: To quantify the articulatory distinctiveness of 8 major English vowels and 11 English consonants based on tongue and lip movement time series data using a data-driven approach.Method: Tongue and lip movements of 8 vowels and 11 consonants from 10 healthy talkers were collected. First, classification accuracies were obtained using 2 complementary approaches: (a) Procrustes analysis and (b) a support vector machine. Procrustes distance was then used to measure the articulatory distinctiveness among vowels and consonants. Finally, the distance (distinctiveness) matrices of different vowel pairs and consonant pairs were used to derive articulatory vowel and consonant spaces using multidimensional scaling. Results: Vowel classification accuracies of 91.67% and 89.05% and consonant classification accuracies of 91.37% and 88.94% were obtained using Procrustes analysis and a support vector machine, respectively. Articulatory vowel and consonant spaces were derived based on the pairwise Procrustes distances. Conclusions: The articulatory vowel space derived in this study resembled the long-standing descriptive articulatory vowel space defined by tongue height and advancement. The articulatory consonant space was consistent with feature-based classification of English consonants. The derived articulatory vowel and consonant spaces may have clinical implications, including serving as an objective measure of the severity of articulatory impairment. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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