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Voice Pathologies Identification Speech signals, features and classifiers evaluation

2015-12-28Conference object Restricted access
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dc.contributor.authorCordeiro, Hugo
dc.contributor.authorFonseca, José
dc.contributor.authorGuimarães, Isabel
dc.contributor.authorMeneses, Carlos
dc.date.accessioned2019-02-15T09:58:41Z
dc.date.available2019-02-15T09:58:41Z
dc.date.issued2015-12-28
dc.description.abstractVoice pathology identification using speech processing methods can be used as a preliminary diagnosis. This study implements a set of identification systems to screen voice pathologies using voice signal features from the sustained vowel /a/ and continuous speech. The two signals tasks are evaluated using three acoustic features applied to four classifiers. Three main classes are identified: physiological disorders; neuromuscular disorders; and healthy subjects. The main objective of this work is to evaluate which voice signal is more reliable for voice pathology diagnosis, which acoustic feature has more pathology information and which is the best classifier to carry out this task. The best overall system accuracy is 77.9%, obtained with Mel-Line Spectrum Frequencies (MLSF) feature extracted from continuous speech and applied to a Gaussian Mixture Models (GMM) classifier.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationVoice Pathologies Identification Speech signals, features and classifiers evaluation. In SPA 2015 Signal Processing Algorithms, Architectures, Arrangements, and Applications. Poznan, Poland: IEEE, 2015. ISBN 978-8-3620-6523-3. Pp. 81-86pt_PT
dc.identifier.doi10.1109/SPA.2015.7365138pt_PT
dc.identifier.isbn978-8-3620-6523-3
dc.identifier.isbn978-8-3620-6522-6
dc.identifier.issn2326-0319
dc.identifier.issn2326-0262
dc.identifier.urihttp://hdl.handle.net/10400.21/9503
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherInstitute of Electrical and Electronics Engineerspt_PT
dc.relation.publisherversionhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7365138pt_PT
dc.subjectComponentpt_PT
dc.subjectVoice Pathologies Identificationpt_PT
dc.subjectContinuous Speechpt_PT
dc.subjectSustained Vowelpt_PT
dc.subjectMLSFpt_PT
dc.subjectGMMpt_PT
dc.titleVoice Pathologies Identification Speech signals, features and classifiers evaluationpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlace23-25 Sept. 2015 - Poznan, Polandpt_PT
oaire.citation.endPage86pt_PT
oaire.citation.startPage81pt_PT
oaire.citation.titleSPA 2015 Signal Processing Algorithms, Architectures, Arrangements, and Applicationspt_PT
person.familyNameCordeiro
person.familyNameGuimarães
person.familyNameMeneses
person.givenNameHugo
person.givenNameIsabel
person.givenNameCarlos
person.identifier548796
person.identifier.ciencia-idA81E-0891-9E9C
person.identifier.ciencia-idF014-BFD6-49C2
person.identifier.ciencia-id531B-D2F8-2544
person.identifier.orcid0000-0001-5559-7746
person.identifier.orcid0000-0001-8524-8731
person.identifier.orcid0000-0002-7770-7093
person.identifier.ridQ-4604-2019
person.identifier.scopus-author-id15833754300
person.identifier.scopus-author-id24586862700
rcaap.rightsclosedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationd89b5aa9-55f3-4087-80d4-ab6a005906d6
relation.isAuthorOfPublication01022df5-418d-4c3b-a61a-2352021b43dd
relation.isAuthorOfPublication97333978-1ce6-4d9a-9639-dc014f9e4ff3
relation.isAuthorOfPublication.latestForDiscovery97333978-1ce6-4d9a-9639-dc014f9e4ff3

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