Unveiling Vocal Phenotypes of Dysphonia with Unsupervised Learning

Federico Calà, Francesco Correnti, Lorenzo Frassineti, Giovanna Cantarella, Giovanna Cantarella, Giulia Buccichini, Ludovica Battilocchi, Antonio Lanatà

2025

Abstract

Dysphonia is a voice disorder caused by morphological and neurological alterations. This work proposes a clustering analysis on vocal properties of patients diagnosed with benign lesions of the vocal folds (BLVF) and unilateral vocal fold paralysis (UVFP) to identify if they constitute separate vocal subtypes of dysphonia and to understand whether misclustered data depend on a specific diagnosis and age. Two hundred seventy-five patients uttered a sustained vowel /a/, from which acoustic features were extracted and transformed. Two conditions were tested separately for each gender: the unaware and the aware approach, where statistical analysis was performed to select the significantly different parameters between BLVF and UVFP. The best clustering results were obtained for the aware condition, with a silhouette score of 0.70 for both genders; accuracies were 0.67 and 0.70 for the female and male patients. A single component was retained for both genders: phonation and articulation parameters presented high weights for female and male patients, respectively. Misclustered observations analysis showed that feature transformation and reduction improved the UVFP voices clusterability. The clustering error outcome did not depend on age, voice disorder types, or subtypes. These findings may contribute to a better understanding of voice disorders’ properties, reducing misdiagnoses and supporting their follow-up.

Paper Citation

in Harvard Style

Calà F., Correnti F., Frassineti L., Cantarella G., Buccichini G., Battilocchi L. and Lanatà A. (2025). Unveiling Vocal Phenotypes of Dysphonia with Unsupervised Learning. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS; ISBN 978-989-758-731-3, SciTePress, pages 860-867. DOI: 10.5220/0013132200003911

in Bibtex Style

@conference{biosignals25,
author={Federico Calà and Francesco Correnti and Lorenzo Frassineti and Giovanna Cantarella and Giulia Buccichini and Ludovica Battilocchi and Antonio Lanatà},
title={Unveiling Vocal Phenotypes of Dysphonia with Unsupervised Learning},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS},
year={2025},
pages={860-867},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013132200003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS
TI - Unveiling Vocal Phenotypes of Dysphonia with Unsupervised Learning
SN - 978-989-758-731-3
AU - Calà F.
AU - Correnti F.
AU - Frassineti L.
AU - Cantarella G.
AU - Buccichini G.
AU - Battilocchi L.
AU - Lanatà A.
PY - 2025
SP - 860
EP - 867
DO - 10.5220/0013132200003911
PB - SciTePress