Clustering of Voice Pathologies based on Sustained Voice Parameters

Alessa Anjos de Oliveira, Alessa Anjos de Oliveira, Maria E. Dajer, Paula O. Fernandes, Paula O. Fernandes, João Paulo Teixeira, João Paulo Teixeira, João Paulo Teixeira

2020

Abstract

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.

Paper Citation

in Harvard Style

Anjos de Oliveira A., Dajer M., Fernandes P. and Teixeira J. (2020). Clustering of Voice Pathologies based on Sustained Voice Parameters. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 4: BIOSIGNALS; ISBN 978-989-758-398-8, SciTePress, pages 280-287. DOI: 10.5220/0009146202800287

in Bibtex Style

@conference{biosignals20,
author={Alessa Anjos de Oliveira and Maria E. Dajer and Paula O. Fernandes and João Paulo Teixeira},
title={Clustering of Voice Pathologies based on Sustained Voice Parameters},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 4: BIOSIGNALS},
year={2020},
pages={280-287},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009146202800287},
isbn={978-989-758-398-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 4: BIOSIGNALS
TI - Clustering of Voice Pathologies based on Sustained Voice Parameters
SN - 978-989-758-398-8
AU - Anjos de Oliveira A.
AU - Dajer M.
AU - Fernandes P.
AU - Teixeira J.
PY - 2020
SP - 280
EP - 287
DO - 10.5220/0009146202800287
PB - SciTePress