Multiple voice disorders in the same individual: Investigating handcrafted features, multi-label classification algorithms, and base-learners

Non-invasive acoustic analyses of voice disorders have been at the forefront of current biomedical research. Usual strategies, essentially based on machine learning (ML) algorithms, commonly classify a subject as being either healthy or pathologically-affected. Nevertheless, the latter state is not...

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Vydáno v:	Speech communication Ročník 152; s. 102952
Hlavní autoři:	Barbon, Sylvio, Guido, Rodrigo Capobianco, Aguiar, Gabriel Jonas, Santana, Everton José, Proença, Mario Lemes, Patil, Hemant A.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.07.2023
Témata:	Deep learning Handcrafted feature extraction Multi-label classification Multiple voice disorders Deep learning Multiple voice disorders Handcrafted feature extraction Multi-label classification
ISSN:	0167-6393, 1872-7182
On-line přístup:	Získat plný text
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