Panel The integration of voice science, voice pathology, medicine, public speaking, acting, and singing

Scherer, Ronald C.; Brewer, David; Colton, Raymond H.; Rubin, Lucille S.; Raphael, Bonnie N.; Miller, Richard J.; Howell, Elizabeth; Ge, Moore

doi:10.1016/s0892-1997(05)80285-1

Cited by 5 publications

(3 citation statements)

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“…This illustrates that the transition between both voice structures can be fluid. On the other hand, close attention must be paid to whether the demands of the respective fach on the vocal folds are manageable for the performers [48][49][50][51]. This applies in particular to the frequently observed development from the lyric to the dramatic fach [33].…”

Section: Discussionmentioning

confidence: 99%

Harnessing Machine Learning in Vocal Arts Medicine: A Random Forest Application for “Fach” Classification in Opera

Wang,

Müller,

Caffier

et al. 2023

Diagnostics

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Vocal arts medicine provides care and prevention strategies for professional voice disorders in performing artists. The issue of correct “Fach” determination depending on the presence of a lyric or dramatic voice structure is of crucial importance for opera singers, as chronic overuse often leads to vocal fold damage. To avoid phonomicrosurgery or prevent a premature career end, our aim is to offer singers an improved, objective fach counseling using digital sound analyses and machine learning procedures. For this purpose, a large database of 2004 sound samples from professional opera singers was compiled. Building on this dataset, we employed a classic ensemble learning method, namely the Random Forest algorithm, to construct an efficient fach classifier. This model was trained to learn from features embedded within the sound samples, subsequently enabling voice classification as either lyric or dramatic. As a result, the developed system can decide with an accuracy of about 80% in most examined voice types whether a sound sample has a lyric or dramatic character. To advance diagnostic tools and health in vocal arts medicine and singing voice pedagogy, further machine learning methods will be applied to find the best and most efficient classification method based on artificial intelligence approaches.

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Section: Discussionmentioning

confidence: 99%

Harnessing Machine Learning in Vocal Arts Medicine: A Random Forest Application for “Fach” Classification in Opera

Wang,

Müller,

Caffier

et al. 2023

Diagnostics

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“…41 This study has been effective in applying scientific measurements to the voice as it is used in live theatrical performance. It shows that group of actors using La MaMa vocal technique were able to engage in extended voice use in extreme conditions over a period of 6 weeks without damage to the voice, as evidenced by acoustic and perceptual data.…”

Section: Discussionmentioning

confidence: 99%

“…David W. Brewer urged collaboration for the mutual advancement of both professions: ''Only by continuing an increased collaboration can scientists, teachers and artists hope to identify the best training techniques as well as the causes and most efficacious treatments of our many vocal ills.'' 41 …”

Section: Discussionmentioning

confidence: 99%

The Impact of Extended Voice Use on the Acoustic Characteristics of Phonation After Training and Performance of Actors From the La MaMa Experimental Theater Club

2011

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The effects of preventive vocal hygiene education on the vocal hygiene habits and perceptual vocal characteristics of training singers

Broaddus-Lawrence¹,

Treole²,

McCabe³

et al. 2000

Journal of Voice

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Panel The integration of voice science, voice pathology, medicine, public speaking, acting, and singing

Cited by 5 publications

References 0 publications

Harnessing Machine Learning in Vocal Arts Medicine: A Random Forest Application for “Fach” Classification in Opera

Harnessing Machine Learning in Vocal Arts Medicine: A Random Forest Application for “Fach” Classification in Opera

The Impact of Extended Voice Use on the Acoustic Characteristics of Phonation After Training and Performance of Actors From the La MaMa Experimental Theater Club

The effects of preventive vocal hygiene education on the vocal hygiene habits and perceptual vocal characteristics of training singers

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