2001
DOI: 10.1016/s0165-5876(00)00411-0
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Acoustic analysis in the diagnosis of voice disorders in children

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Cited by 50 publications
(37 citation statements)
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“…The high prevalence of childhood dysphonia mandates that special attention be paid to the evaluation and diagnosis of children's voices, with objective measures to enable an understanding of the severity of the voice deviance and how it manifests itself at different stages between the ages of 3 and 9 years 1,[19][20][21] .…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…The high prevalence of childhood dysphonia mandates that special attention be paid to the evaluation and diagnosis of children's voices, with objective measures to enable an understanding of the severity of the voice deviance and how it manifests itself at different stages between the ages of 3 and 9 years 1,[19][20][21] .…”
Section: Discussionmentioning
confidence: 99%
“…Typically, incomplete glottal closure due to alterations in the glottal proportions, as is the case with a child's larynx, can generate hyperfunction of the phonatory mechanism in an attempt to increase voice loudness, especially in group activities and in the presence of competing noise in the environment 19 . Strained voice production by children is consistent with a hyperfunctional voice pattern, which may be related to recurring lower airway infections, social determinants, or anatomic and behavioral characteristics 1,22 .…”
Section: In the χmentioning
confidence: 99%
“…Several studies [19] [20] [21] [22] have investigated the characteristics of speech features in speakers with speech impairments. Speech features of speech impairments vary with the changes within the vocal organs [20].…”
Section: Research Backgroundmentioning
confidence: 99%
“…Speech features of speech impairments vary with the changes within the vocal organs [20]. The selected features are defined as follows:…”
Section: Research Backgroundmentioning
confidence: 99%
“…Large number studies have been carried out for objective analysis of voice. But most of these studies are focused on analysing the acoustic features which are highly person specific like jitter, pitch, tone using mathematical signal processing techniques [9][10][11]. There are various frameworks of voice signal analysis being used by researchers like for mood identification, emotion recognition, disease classification etc [12][13][14][15], however, many of frameworks that are in practice today, are based on Jitter, Shimmer, Pitch Tone which are highly user specific due to which it cannot be generalised for analysis of individuals [16].…”
Section: Introductionmentioning
confidence: 99%