Voice, Speech, and Language Problems in the U.S. Pediatric Population: The 2012 National Health Interview Survey (NHIS).

Hoffman, Howard J.; Li, C. M.; Bainbridge, Kathleen E.; Losonczy, Katalin G.; Chiu, May S.; Rice, Mabel L.

doi:10.1093/ije/dyv096.489

Cited by 6 publications

(1 citation statement)

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“…An estimated 17.9 million U.S. adults of ages 18 or older report voice problems in a year [1], [2]. Among them, approximately 9.4 million adults are having problems using their voice that lasts for one week or longer [3]. According to a recent report, published by the National Center for Education Statistics, about 20% of children and youth in the age group of 3-21 years suffer from voice disability [4].…”

Section: Introductionmentioning

confidence: 99%

A Survey on Signal Processing Based Pathological Voice Detection Techniques

2020

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Voice disability is a barrier to effective communication. Around 1.2% of the World's population is facing some form of voice disability. Surgical procedures namely laryngoscopy, laryngeal electromyography, and stroboscopy are used for voice disability diagnosis. Researchers and practitioners have been working to find alternatives to these surgical procedures. Voice sample based diagnosis is one of them. The major steps followed by these works are (a) to extract voice features from voice samples and (b) to discriminate pathological voices from normal voices by using a classifier algorithm. However, there is no consensus about the voice feature and the classifier algorithm that can provide the best accuracy in screening voice disability. Moreover, some of the works use multiple voice features and multiple classifiers to ensure high reliability. In this paper, we address these issues. The motivation of the work is to address the need for non-invasive signal processing techniques to detect voice disability in the general population. This paper conducts a survey related to voice disability detection methods. The paper contains two main parts. In the first part, we present background information including causes of voice disability, current procedures and practices, voice features, and classifiers. In the second part, we present a comprehensive survey work on voice disability detection algorithms. The issues and challenges related to the selection of voice feature and classifier algorithms have been addressed at the end of this paper. INDEX TERMS Algorithms, issues and challenges, signal processing, surgical methods, survey, voice disability, voice features.

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Section: Introductionmentioning

confidence: 99%