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Clustering of voice pathologies based on sustained voice parameters

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Resumo:Signal processing techniques can be used to extract information that contribute to the detection of laryngeal disorders. The goal of this paper is to perform a statistical analysis through the boxplot tool from 832 voice signals of individuals with different laryngeal pathologies from the Saarbrücken Voice Database in order to create relevant groups, making feasible an automatic identification of these dysfunctions. Jitter, Shimmer, HNR, NHR and Autocorrelation features were compared between several groups of voice pathologies/conditions, resulting in three identified clusters.
Autores principais:Oliveira, Alessa Anjos de
Outros Autores:Dajer, Maria; Fernandes, Paula Odete; Teixeira, João Paulo
Assunto:Voice pathologies clustering Clustering with boxplot Voice pathologies analysis Jitter shimmer HNR Autocorrelation statistical analysis
Ano:2020
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB

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