loading
Papers Papers/2020

Research.Publish.Connect.

Paper

Authors: Alessa de Oliveira 1 ; 2 ; Maria Dajer 1 and João Teixeira 2

Affiliations: 1 Federal University of Technology of Paraná, Campus Cornélio Procópio, 86300 000, Cornélio Procópio, Brazil ; 2 Research Centre in Digitalization and Intelligent Robotics (CEDRI), Instituto Politecnico de Braganca, Campus Sta. Apolonia, 5301 857, Braganca, Portugal

ISBN: 978-989-758-490-9

ISSN: 2184-4305

Keyword(s): Acoustic Parameters, Clustering, Hierarchical Clustering, Kohonen's Self-Organizing Maps, Unsupervised Artificial Neural Networks, Voice Pathologies.

Abstract: The main purpose of clustering voice pathologies is the attempt to form large groups of subjects with similar pathologies to be used with Deep-Learning. This paper focuses on applying Kohonen's Self-Organizing Maps and Hierarchical Clustering to investigate how these methods behave in the clustering procedure of voice samples by means of the parameters absolute jitter, relative jitter, absolute shimmer, relative shimmer, HNR, NHR and Autocorrelation. For this, a comparison is made between the speech samples of the Control group of subjects, the Hyper-functional Dysphonia and Vocal Folds Paralysis pathologies groups of subjects. As a result, the dataset was divided in two clusters, with no distinction between the pre-defined groups of pathologies. The result is aligned with previous result using statistical analysis.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.207.132.116

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
de Oliveira, A.; Dajer, M. and Teixeira, J. (2021). Clustering Pathologic Voice with Kohonen SOM and Hierarchical Clustering . In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSIGNALS, ISBN 978-989-758-490-9; ISSN 2184-4305, pages 158-163. DOI: 10.5220/0010210901580163

@conference{biosignals21,
author={Alessa {de Oliveira}. and Maria Dajer. and João Teixeira.},
title={Clustering Pathologic Voice with Kohonen SOM and Hierarchical Clustering },
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSIGNALS,},
year={2021},
pages={158-163},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010210901580163},
isbn={978-989-758-490-9},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSIGNALS,
TI - Clustering Pathologic Voice with Kohonen SOM and Hierarchical Clustering
SN - 978-989-758-490-9
IS - 2184-4305
AU - de Oliveira, A.
AU - Dajer, M.
AU - Teixeira, J.
PY - 2021
SP - 158
EP - 163
DO - 10.5220/0010210901580163

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.
0123movie.net