Literature DB >> 7283066

Professional singers: the science and art of clinical care.

R T Sataloff.   

Abstract

Voice complaints of serious singers are usually not imaginary, and rational diagnosis and treatment can be achieved through systematic inquiry and analysis based on anatomy, physiology, psychology and psychoacoustics of voice production. Good vocal habits should be encouraged from childhood. Measures to aid in voice conservation include avoiding singing in noisy, dry, dusty, and smoky environments and learning to control the voice in circumstances in which auditory monitoring of the intensity of vocalization cannot be done effectively. The dangers of cheerleading, choir-conducting, and other forms of abuse of the speaking voice for the serious singer are emphasized. Young singers should be enthusiastically encouraged to sing music suitable for their ages and voices, and should be discouraged from taking on difficult roles prematurely. Smoking must be avoided. Thorough training and regular practice are essential for maintenance of a healthy singing voice. Close cooperation among laryngologist, speech pathologist and voice teacher is emphasized. Treatments for reflux laryngitis, anxiety, muscle spasm, voice abuse, vocal nodules, and infectious laryngitis in the professional singer are detailed.

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Mesh:

Year:  1981        PMID: 7283066     DOI: 10.1016/s0196-0709(81)80022-1

Source DB:  PubMed          Journal:  Am J Otolaryngol        ISSN: 0196-0709            Impact factor:   1.808


  4 in total

1.  Managing dysphonia caused by misuse and overuse.

Authors:  P Carding; A Wade
Journal:  BMJ       Date:  2000 Dec 23-30

2.  Changes in voice characteristics after uvulopalatopharyngoplasty.

Authors:  H Rihkanen; I Soini
Journal:  Eur Arch Otorhinolaryngol       Date:  1992       Impact factor: 2.503

3.  Quantifying Laryngopharyngeal Reflux in Singers: Perceptual and Objective Findings.

Authors:  Adam T Lloyd; Bari Hoffman Ruddy; Erin Silverman; Vicki M Lewis; Jeffrey J Lehman
Journal:  Biomed Res Int       Date:  2017-09-19       Impact factor: 3.411

4.  Paralinguistic singing attribute recognition using supervised machine learning for describing the classical tenor solo singing voice in vocal pedagogy.

Authors:  Yanze Xu; Weiqing Wang; Huahua Cui; Mingyang Xu; Ming Li
Journal:  EURASIP J Audio Speech Music Process       Date:  2022-04-15
  4 in total

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