An immunological approach based on the negative selection algorithm for real noise classification in speech signals

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dc.contributor.authorAbreu, Caio Cesar Enside de [UNESP]
dc.contributor.authorDuarte, Marco Aparecido Queiroz
dc.contributor.authorVillarreal, Francisco [UNESP]
dc.contributor.institutionState University of Mato Grosso - UNEMAT
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade Estadual de Mato Grosso do Sul (UEMS)
dc.date.accessioned2018-12-11T17:09:14Z
dc.date.available2018-12-11T17:09:14Z
dc.date.issued2017-02-01
dc.description.abstractThis paper presents a new approach to detect and classify background noise in speech sentences based on the negative selection algorithm and dual-tree complex wavelet transform. The energy of the complex wavelet coefficients across five wavelet scales are used as input features. Afterward, the proposed algorithm identifies whether the speech sentence is, or is not, corrupted by noise. In the affirmative case, the system returns the type of the background noise amongst the real noise types considered. Comparisons with classical supervised learning methods are carried out. Simulation results show that the artificial immune system proposed overcomes classical classifiers in accuracy and capacity of generalization. Future applications of this tool will help in the development of new speech enhancement or automatic speech recognition systems based on noise classification.en
dc.description.affiliationState University of Mato Grosso - UNEMAT Department of Computing, Santa Rita Street 128
dc.description.affiliationSão Paulo State University - UNESP Department of Electrical Engineering, Brasil Avenue 56, Ilha Solteira
dc.description.affiliationState University of Mato Grosso do Sul - UEMS Department of Mathematics, Rodovia MS 306 KM 06, Cassilândia
dc.description.affiliationSão Paulo State University - UNESP Department of Mathematics, Brasil Avenue 56, Ilha Solteira
dc.description.affiliationUnespSão Paulo State University - UNESP Department of Electrical Engineering, Brasil Avenue 56, Ilha Solteira
dc.description.affiliationUnespSão Paulo State University - UNESP Department of Mathematics, Brasil Avenue 56, Ilha Solteira
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipIdCAPES: 2011/17610-0
dc.format.extent125-133
dc.identifierhttp://dx.doi.org/10.1016/j.aeue.2016.12.004
dc.identifier.citationAEU - International Journal of Electronics and Communications, v. 72, p. 125-133.
dc.identifier.doi10.1016/j.aeue.2016.12.004
dc.identifier.issn1618-0399
dc.identifier.issn1434-8411
dc.identifier.scopus2-s2.0-85009388627
dc.identifier.urihttp://hdl.handle.net/11449/174078
dc.language.isoeng
dc.relation.ispartofAEU - International Journal of Electronics and Communications
dc.relation.ispartofsjr0,420
dc.rights.accessRightsAcesso restrito
dc.sourceScopus
dc.subjectArtificial immune systems
dc.subjectDual-tree complex wavelet transform
dc.subjectNegative selection algorithm
dc.subjectNoise classification
dc.subjectSpeech enhancement
dc.titleAn immunological approach based on the negative selection algorithm for real noise classification in speech signalsen
dc.typeArtigo

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Artigos - Engenharia Elétrica - FEIS
Artigos - Matemática - FEIS