Clustering of voice pathologies based on sustained voice parameters

Oliveira, Alessa Anjos de; Dajer, Maria; Fernandes, Paula Odete; Teixeira, João Paulo

http://hdl.handle.net/10198/26898

Use this identifier to reference this record.

Name:	Description:	Size:	Format:
BIOSIGNALS_2020_40 (1)_SCITePRESS.pdf		579.79 KB	Adobe PDF	Download

Send Feedback

Authors

Oliveira, Alessa Anjos de

Dajer, Maria

Fernandes, Paula Odete

Teixeira, João Paulo

Abstract(s)

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.

Keywords

Voice pathologies clustering Clustering with boxplot Voice pathologies analysis Jitter shimmer HNR Autocorrelation statistical analysis

URI

http://hdl.handle.net/10198/26898

Citation

Oliveira, Alessa Anjos de; Dajer, Maria; Fernandes, Paula O.; Teixeira, João Paulo (2020). Clustering of voice pathologies based on sustained voice parameters. In 13th International Joint Conference on Biomedical Engineering Systems and Technologies. Malta. ISSN 2184-4305. 4: p. 280-287