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Autor/inn/enWang, Jun; Samal, Ashok; Rong, Panying; Green, Jordan R.
TitelAn Optimal Set of Flesh Points on Tongue and Lips for Speech-Movement Classification
QuelleIn: Journal of Speech, Language, and Hearing Research, 59 (2016) 1, S.15-26 (12 Seiten)
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1092-4388
DOI10.1044/2015_JSLHR-S-14-0112
SchlagwörterSpeech Communication; Human Body; Measurement Equipment; Articulation (Speech); Phonemes; Classification
AbstractPurpose: The authors sought to determine an optimal set of flesh points on the tongue and lips for classifying speech movements. Method: The authors used electromagnetic articulographs (Carstens AG500 and NDI Wave) to record tongue and lip movements from 13 healthy talkers who articulated 8 vowels, 11 consonants, a phonetically balanced set of words, and a set of short phrases during the recording. We used a machine-learning classifier (support-vector machine) to classify the speech stimuli on the basis of articulatory movements. We then compared classification accuracies of the flesh-point combinations to determine an optimal set of sensors. Results: When data from the 4 sensors (T1: the vicinity between the tongue tip and tongue blade; T4: the tongue-body back; UL: the upper lip; and LL: the lower lip) were combined, phoneme and word classifications were most accurate and were comparable with the full set (including T2: the tongue-body front; and T3: the tongue-body front). Conclusion: We identified a 4-sensor set-that is, T1, T4, UL, LL--that yielded a classification accuracy (91%-95%) equivalent to that using all 6 sensors. These findings provide an empirical basis for selecting sensors and their locations for scientific and emerging clinical applications that incorporate articulatory movements. (As Provided).
AnmerkungenAmerican Speech-Language-Hearing Association. 2200 Research Blvd #250, Rockville, MD 20850. Tel: 301-296-5700; Fax: 301-296-8580; e-mail: slhr@asha.org; Web site: http://jslhr.pubs.asha.org
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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