Clustering of Voice Pathologies based on Sustained Voice Parameters

Alessa Anjos de Oliveira, Maria Dajer, Paula Fernandes, João Teixeira

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.

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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 - Volume 4: BIOSIGNALS, ISBN 978-989-758-398-8, pages 280-287. DOI: 10.5220/0009146202800287


in Bibtex Style

@conference{biosignals20,
author={Alessa Anjos de Oliveira and Maria Dajer and Paula Fernandes and João 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 - 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 - 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