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Speech Denoising Using Non-Negative Matrix Factorization with Kullback-Leibler Divergence and Sparseness Constraints

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dc.affiliation.dptoUC3M. Departamento de Teoría de la Señal y Comunicacioneses
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Procesado Multimediaes
dc.contributor.authorGallardo Antolín, Ascensiónes
dc.contributor.authorLudeña Choez, Jimmy D.
dc.date.accessioned2015-10-05T10:00:59Z
dc.date.available2015-10-05T10:00:59Z
dc.date.issued2012
dc.descriptionProceedings of: IberSPEECH 2012 Conference, Madrid, Spain, November 21-23, 2012.en
dc.description.abstractA speech denoising method based on Non-Negative Matrix Factorization (NMF) is presented in this paper. With respect to previous related works, this paper makes two contributions. First, our method does not assume a priori knowledge about the nature of the noise. Second, it combines the use of the Kullback-Leibler divergence with sparseness constraints on the activation matrix, improving the performance of similar techniques that minimize the Euclidean distance and/or do not consider any sparsification. We evaluate the proposed method for both, speech enhancement and automatic speech recognitions tasks, and compare it to conventional spectral subtraction, showing improvements in speech quality and recognition accuracy, respectively, for different noisy conditions.en
dc.description.sponsorshipThis work has been partially supported by the Spanish Government grants TSI-020110-2009-103 and TEC2011-26807.en
dc.description.statusPublicadoes
dc.format.extent10
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationTorre Toledano, D., et al. (eds.) Advances in Speech and Language Technologies for Iberian Languages: IberSPEECH 2012 Conference, Madrid, Spain, November 21-23, 2012. Proceedings. (pp. 207-216). (Communications in Computer and Information Science; 328). Springer Berlin Heidelberg.en
dc.identifier.doi10.1007/978-3-642-35292-8_22
dc.identifier.isbn978-3-642-35292-8 (online)
dc.identifier.isbn978-3-642-35291-1 (print)
dc.identifier.issn1865-0929
dc.identifier.publicationfirstpage207es
dc.identifier.publicationlastpage216es
dc.identifier.publicationtitleAdvances in Speech and Language Technologies for Iberian Languages: IberSPEECH 2012 Conference, Madrid, Spain, November 21-23, 2012. Proceedingsen
dc.identifier.publicationvolume328
dc.identifier.urihttps://hdl.handle.net/10016/21659
dc.identifier.uxxiCC/0000017366
dc.language.isoengen
dc.publisherSpringeren
dc.relation.eventdate2012-11-21en
dc.relation.eventnumber7
dc.relation.eventplaceMadrides
dc.relation.eventtitleIberSPEECH 2012 Conference: VII Jornadas en Tecnología del Habla and III Iberian SLTECH Workshopen
dc.relation.ispartofseriesCommunications in Computer and Information Scienceen
dc.relation.projectIDGobierno de España. TSI-020110-2009-103es
dc.relation.projectIDGobierno de España. TEC2011-26807es
dc.relation.publisherversionhttp://dx.doi.org/10.1007/978-3-642-35292-8_22es
dc.rights© 2012 Springer-Verlag Berlin Heidelbergen
dc.rights.accessRightsopen accesses
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherNon-Negative Matrix Factorizationen
dc.subject.otherKullback-Leibler Divergenceen
dc.subject.otherSparseness Constraintsen
dc.subject.otherSpeech Denoisingen
dc.subject.otherSpeech Enhancementen
dc.subject.otherAutomatic Speech Recognitionen
dc.titleSpeech Denoising Using Non-Negative Matrix Factorization with Kullback-Leibler Divergence and Sparseness Constraintsen
dc.typeconference paper*
dc.type.hasVersionAM*
dspace.entity.typePublication
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