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dc.creatorVignolo, Leandro Daniel-
dc.creatorMilone, Diego Humberto-
dc.creatorRufiner, Hugo Leonardo-
dc.date2017-04-03T18:03:57Z-
dc.date2017-04-03T18:03:57Z-
dc.date2013-05-
dc.date2017-03-22T15:19:25Z-
dc.date.accessioned2019-04-29T15:28:16Z-
dc.date.available2019-04-29T15:28:16Z-
dc.date.issued2017-04-03T18:03:57Z-
dc.date.issued2017-04-03T18:03:57Z-
dc.date.issued2013-05-
dc.date.issued2017-03-22T15:19:25Z-
dc.identifierVignolo, Leandro Daniel; Milone, Diego Humberto; Rufiner, Hugo Leonardo; Genetic wavelet packets for speech recognition; Elsevier; Expert Systems With Applications; 40; 6; 5-2013; 2350-2359-
dc.identifier0957-4174-
dc.identifierhttp://hdl.handle.net/11336/14698-
dc.identifier.urihttp://rodna.bn.gov.ar:8080/jspui/handle/bnmm/294713-
dc.descriptionThe most widely used speech representation is based on the mel-frequency cepstral coefficients, which incorporates biologically inspired characteristics into artificial recognizers. However, the recognition performance with these features can still be enhanced, specially in adverse conditions. Recent advances have been made with the introduction of wavelet based representations for different kinds of signals, which have shown to improve the classification performance. However, the problem of finding an adequate wavelet based representation for a particular problem is still an important challenge. In this work we propose a genetic algorithm to evolve a speech representation, based on a non-orthogonal wavelet decomposition, for phoneme classification. The results, obtained for a set of spanish phonemes, show that the proposed genetic algorithm is able to find a representation that improves speech recognition results. Moreover, the optimized representation was evaluated in noise conditions.-
dc.descriptionFil: Vignolo, Leandro Daniel. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnológico Santa Fe. Instituto de Investigacion en Señales, Sistemas e Inteligencia Computacional; Argentina; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina-
dc.descriptionFil: Milone, Diego Humberto. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnológico Santa Fe. Instituto de Investigacion en Señales, Sistemas e Inteligencia Computacional; Argentina; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina-
dc.descriptionFil: Rufiner, Hugo Leonardo. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnológico Santa Fe. Instituto de Investigacion en Señales, Sistemas e Inteligencia Computacional; Argentina; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina-
dc.formatapplication/pdf-
dc.formatapplication/pdf-
dc.languageeng-
dc.publisherElsevier-
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.eswa.2012.10.050-
dc.relationinfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0957417412011748-
dc.rightsinfo:eu-repo/semantics/restrictedAccess-
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/-
dc.sourcereponame:CONICET Digital (CONICET)-
dc.sourceinstname:Consejo Nacional de Investigaciones Científicas y Técnicas-
dc.sourceinstacron:CONICET-
dc.subjectPhoneme classification-
dc.subjectgenetic algorithms-
dc.subjectwrappers-
dc.subjectwavelet packets-
dc.subjectIngeniería de Sistemas y Comunicaciones-
dc.subjectIngeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información-
dc.subjectINGENIERÍAS Y TECNOLOGÍAS-
dc.titleGenetic wavelet packets for speech recognition-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.typeinfo:ar-repo/semantics/articulo-
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