research-article

Voice signal features analysis and classification: looking for new diseases related parameters

Authors:

Giuseppe Tradigo,

Barbara Calabrese,

Manuela Macrí,

Eugenio Vocaturo,

Nicola Lombardo,

Pierangelo VeltriAuthors Info & Claims

BCB '15: Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics

Pages 589 - 596

https://doi.org/10.1145/2808719.2812222

Published: 09 September 2015 Publication History

Abstract

Dysphonia is an often-underestimated vocal tract problem caused by irregular vocal cords vibration. It has been proved that dysphonia can be considered as a symptom of vocal tract diseases; also, voice anomalies represent neurological or neurodegenerative diseases triggers. Indeed, dysarthric voice patterns are studied as early detection for Parkinson's syndrome. Voice acoustic features can thus be extracted from simple vocalism (or short reading) and considered as diseases indicators. The interest is also improved thank to the possibility of using mobile and/or portable technologies to analyze voice parameters in a background manner. Nevertheless, voice can be considered as a personal signature, thus the identification of a general purpose features identification is still an open issue.

In this work we focus on identifying voice signal features by using a comparative study of different classifiers. The target is to identify frequencies values and noise indexes (or combination of them) to be used as general purpose indicators, aiming to discriminate between healthy and pathological voices. The work is part of a larger project on voice analysis aiming to define a mobile and reliable based system allowing the acquisition and features extraction of vocal signals to be used as healthy monitor.

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https://doi.org/10.1007/s11042-023-17885-3
Singhal ASharma D(2023)Voice signal-based disease diagnosis using IoT and learning algorithms for healthcareImplementation of Smart Healthcare Systems using AI, IoT, and Blockchain10.1016/B978-0-323-91916-6.00005-9(59-81)Online publication date: 2023
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Index Terms

Voice signal features analysis and classification: looking for new diseases related parameters
1. Applied computing
  1. Life and medical sciences

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cover image ACM Conferences

BCB '15: Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics

September 2015

683 pages

ISBN:9781450338530

DOI:10.1145/2808719

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 09 September 2015

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BCB '15: ACM International Conference on Bioinformatics, Computational Biology and Biomedicine

September 9 - 12, 2015

Georgia, Atlanta

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BCB '15 Paper Acceptance Rate 48 of 141 submissions, 34%;

Overall Acceptance Rate 254 of 885 submissions, 29%

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Cited By

King SPinder SFernandez-Lanvin DGonzález García CDe Andrés JLabrador M(2024)Noise signature identification using mobile phones for indoor localizationMultimedia Tools and Applications10.1007/s11042-023-17885-3Online publication date: 16-Jan-2024
https://doi.org/10.1007/s11042-023-17885-3
Singhal ASharma D(2023)Voice signal-based disease diagnosis using IoT and learning algorithms for healthcareImplementation of Smart Healthcare Systems using AI, IoT, and Blockchain10.1016/B978-0-323-91916-6.00005-9(59-81)Online publication date: 2023
https://doi.org/10.1016/B978-0-323-91916-6.00005-9
Lombardo NPiazzetta GLobello NPelaia CLongo FTesta DIonna FPelaia GPassali DMotta G(2021)Speech outcome in tongue cancer surgery: objective evaluation by acoustic analysis softwareRomanian Journal of Rhinology10.2478/rjr-2021-002511:44(143-152)Online publication date: 3-Nov-2021
https://doi.org/10.2478/rjr-2021-0025
Tradigo GVizza PLambardi PGuzzi PQuattrone AVeltri PShehu AWu CBoucher CLi JLiu HPop M(2018)A Voice-Aware System for Vocal WellnessProceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics10.1145/3233547.3233729(693-698)Online publication date: 15-Aug-2018
https://dl.acm.org/doi/10.1145/3233547.3233729
Ali ZHossain MMuhammad GSangaiah A(2018)An intelligent healthcare system for detection and classification to discriminate vocal fold disordersFuture Generation Computer Systems10.1016/j.future.2018.02.02185(19-28)Online publication date: Aug-2018
https://doi.org/10.1016/j.future.2018.02.021
Basit MLiu CZhao E(undefined)Sdi: A Tool for Speech Differentiation in User AuthenticationSSRN Electronic Journal10.2139/ssrn.4047897
https://doi.org/10.2139/ssrn.4047897

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