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dc.contributorUniversitat de Vic. Escola Politècnica Superior
dc.contributorUniversitat de Vic. Grup de Recerca en Interaccions Digitals
dc.contributorInternational Conference on Non-Linear Speech Processing NOLISP (2013 : Bèlgica)
dc.contributor.authorSolé-Casals, Jordi
dc.contributor.authorGallego Jutglà, Esteve
dc.contributor.authorMartí i Puig, Pere
dc.contributor.authorTravieso, Carlos M.
dc.contributor.authorAlonso, Jesús B.
dc.date.accessioned2014-01-15T07:58:51Z
dc.date.available2014-01-15T07:58:51Z
dc.date.created2013
dc.date.issued2013
dc.identifier.citationJordi Solé-Casals, Esteve Gallego-Jutglà, Pere Martí-Puig, Carlos M. Travieso, and Jesús B. Alonso (2013). "Speech Enhancement: A Multivariate Empirical Mode Decomposition Approach" A: Lecture Notes in Computer Science, 7911 LNAI, pp. 192-199ca_ES
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/10854/2631
dc.description.abstractSpeech signals in real scenario ambient are usually mixed with some other signals, such as noise. This may interfere with posterior signal processing applied to the signals. In this work, a new technique of data denoising is presented using multivariate Empirical Mode Decomposition. Different SNR ratios are tested in order to study the evolution of the improvement of the recovered data. An improvement of the analyzed data is obtained with all the SNR levels tested.ca_ES
dc.formatapplication/pdf
dc.format.extent8 p.ca_ES
dc.language.isoengca_ES
dc.publisherSpringerca_ES
dc.rights(c) Springer (The original publication is available at www.springerlink.com)
dc.rightsTots els drets reservatsca_ES
dc.subject.otherProcessament de la parlaca_ES
dc.titleSpeech Enhancement: A Multivariate Empirical Mode Decomposition Approachca_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectca_ES
dc.relation.publisherversionhttp://link.springer.com/chapter/10.1007%2F978-3-642-38847-7_25#
dc.rights.accessRightsinfo:eu-repo/semantics/closedAccessca_ES


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