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

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Paper

Clustering of Voice Pathologies based on Sustained Voice Parameters

Topics: Detection and Identification; Medical Signal Acquisition, Analysis and Processing; Pattern Recognition & Machine Learning for Biosignal Data

In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSTEC, 280-287, 2020 , Valletta, Malta

Authors: Alessa Anjos de Oliveira ^{1

;

2} ; Maria E. Dajer ¹ ; Paula O. Fernandes ^{2

;

3} and João Paulo Teixeira ^{2

;

4

;

3}

Affiliations: ¹ Federal University of Technology of Paraná, Campus Cornélio Procópio, 86300 000, Cornélio Procópio, Brazil ; ² Polytechnic Institute of Bragança, Campus Sta. Apolónia, 5301 857 Bragança, Portugal ; ³ Applied Management Research Unit (UNIAG), Bragança 5300, Portugal ; ⁴ Research Centre in Digitalization and Intelligent Robotics (CEDRI), Bragança 5300, Portugal

Keyword(s): Voice Pathologies Clustering, Clustering with Boxplot, Voice Pathologies Analysis, Jitter Shimmer HNR and Autocorrelation Statistical Analysis.

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 several formats:

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) - BIOSIGNALS; ISBN 978-989-758-398-8; ISSN 2184-4305, SciTePress, pages 280-287. DOI: 10.5220/0009146202800287

@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) - BIOSIGNALS},
year={2020},
pages={280-287},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009146202800287},
isbn={978-989-758-398-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - BIOSIGNALS
TI - Clustering of Voice Pathologies based on Sustained Voice Parameters
SN - 978-989-758-398-8
IS - 2184-4305
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