Publication
Hierarchical classification and system combination for automatically identifying physiological and neuromuscular laryngeal pathologies
| dc.contributor.author | Cordeiro, Hugo | |
| dc.contributor.author | Fonseca, Jose | |
| dc.contributor.author | Guimarães, Isabel | |
| dc.contributor.author | Meneses, Carlos | |
| dc.date.accessioned | 2019-03-25T10:54:59Z | |
| dc.date.available | 2019-03-25T10:54:59Z | |
| dc.date.issued | 2017-05 | |
| dc.description.abstract | Objectives. Speech signal processing techniques have provided several contributions to pathologic voice identification, in which healthy and unhealthy voice samples are evaluated. A less common approach is to identify laryngeal pathologies, for which the use of a noninvasive method for pathologic voice identification is an important step forward for preliminary diagnosis. In this study, a hierarchical classifier and a combination of systems are used to improve the accuracy of a three-class identification system (healthy, physiological larynx pathologies, and neuromuscular larynx pathologies). Method. Three main subject classes were considered: subjects with physiological larynx pathologies (vocal fold nodules and edemas: 59 samples), subjects with neuromuscular larynx pathologies (unilateral vocal fold paralysis: 59 samples), and healthy subjects (36 samples). The variables used in this study were a speech task (sustained vowel /a/ or continuous reading speech), features with or without perceptual information, and features with or without direct information about formants evaluated using single classifiers. A hierarchical classification system was designed based on this information. Results. The resulting system combines an analysis of continuous speech by way of the commonly used sustained vowel /a/ to obtain spectral and perceptual speech features. It achieved an accuracy of 84.4%, which represents an improvement of approximately 9% compared with the stand-alone approach. For pathologic voice identification, the accuracy obtained was 98.7%, and the identification accuracy for the two pathology classes was 81.3%. Conclusions. Hierarchical classification and system combination create significant benefits and introduce a modular approach to the classification of larynx pathologies. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | CORDEIRO, Hugo; [et al] – Hierarchical classification and system combination for automatically identifying physiological and neuromuscular laryngeal pathologies. Journal of Voice. ISSN 0892-1997. Vol. 31, N.º 3 (2017), pp. 1-6 | pt_PT |
| dc.identifier.doi | 10.1016/j.jvoice.2016.09.003 | pt_PT |
| dc.identifier.issn | 0892-1997 | |
| dc.identifier.issn | 1873-4588 | |
| dc.identifier.uri | http://hdl.handle.net/10400.21/9772 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Elsevier | pt_PT |
| dc.relation.publisherversion | https://reader.elsevier.com/reader/sd/pii/S089219971630265X?token=D0ADB46DFC970A425DB28CB833F5DC3F3EB7F7B8ED6B09838B66BBC58ECD20D0D5CFA83ED470EF0A6F742F338BD7B75A | pt_PT |
| dc.subject | Hierarchical classification | pt_PT |
| dc.subject | Pathologic voice identification | pt_PT |
| dc.subject | Larynx pathology identification | pt_PT |
| dc.subject | Continuous speech | pt_PT |
| dc.subject | Sustained vowel | pt_PT |
| dc.subject | Classificação hierárquica | pt_PT |
| dc.subject | Identificação de voz patológica | pt_PT |
| dc.subject | Fala contínua | pt_PT |
| dc.title | Hierarchical classification and system combination for automatically identifying physiological and neuromuscular laryngeal pathologies | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 6 | pt_PT |
| oaire.citation.issue | 3 | pt_PT |
| oaire.citation.startPage | 1 | pt_PT |
| oaire.citation.title | Journal of Voice | pt_PT |
| oaire.citation.volume | 31 | pt_PT |
| person.familyName | Cordeiro | |
| person.familyName | Fonseca | |
| person.familyName | Guimarães | |
| person.familyName | Meneses | |
| person.givenName | Hugo | |
| person.givenName | Jose | |
| person.givenName | Isabel | |
| person.givenName | Carlos | |
| person.identifier | 0000000068495282 | |
| person.identifier | 548796 | |
| person.identifier.ciencia-id | A81E-0891-9E9C | |
| person.identifier.ciencia-id | 0F11-7C86-8998 | |
| person.identifier.ciencia-id | F014-BFD6-49C2 | |
| person.identifier.ciencia-id | 531B-D2F8-2544 | |
| person.identifier.orcid | 0000-0001-5559-7746 | |
| person.identifier.orcid | 0000-0001-7173-7374 | |
| person.identifier.orcid | 0000-0001-8524-8731 | |
| person.identifier.orcid | 0000-0002-7770-7093 | |
| person.identifier.rid | Q-4604-2019 | |
| person.identifier.rid | C-9497-2013 | |
| person.identifier.scopus-author-id | 15833754300 | |
| person.identifier.scopus-author-id | 34769664200 | |
| person.identifier.scopus-author-id | 24586862700 | |
| rcaap.rights | closedAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | d89b5aa9-55f3-4087-80d4-ab6a005906d6 | |
| relation.isAuthorOfPublication | 23528527-fe41-4586-84e6-b47523cf4724 | |
| relation.isAuthorOfPublication | 01022df5-418d-4c3b-a61a-2352021b43dd | |
| relation.isAuthorOfPublication | 97333978-1ce6-4d9a-9639-dc014f9e4ff3 | |
| relation.isAuthorOfPublication.latestForDiscovery | 01022df5-418d-4c3b-a61a-2352021b43dd |