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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Electronics and Comm...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Electronics and Communications in Japan
Article . 2018 . Peer-reviewed
License: Wiley Online Library User Agreement
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Tongue habit discrimination system using acoustical feature for oral habits improvement

Authors: Masashi Nakayama; Shunsuke Ishimitsu; Kimiko Yamashita; Kaori Ishii; Kazutaka Kasai; Satoshi Horihata;

Tongue habit discrimination system using acoustical feature for oral habits improvement

Abstract

AbstractOral habits are tongue protrusion in malocclusions, causing deterioration of oral functions necessary for feeding, chewing, swallowing, and vocalization. In order to realize a noninvasive measurement of the habits, we propose and experiment acoustic feature analysis to discriminate tongue habits. Compared to normal speech, tongue‐protruded speech is pronounced between the frontal teeth. The speech is emphasized at a wide‐range band of frequency components due to turbulence, as can be heard in the pronunciation of consonants. In this paper, we confirm these differences in acoustic features, such as zero‐crossing that can capture the characteristics of voiced and unvoiced sounds and Mel Frequency Cepstrum Coefficient (MFCC) that is a filter bank analysis for front‐end processing at speech recognition. We collect samples for that focus on the differences in oral habits of subjects, and significant of acoustic features that measured from the samples are confirmed. Finally, tongue habit discrimination using k‐nearest neighbor algorithm achieved discrimination rate of about 85% to 98% on the databases.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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