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

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dc.contributor.author Gallardo Antolín, Ascensión
dc.contributor.author Ludeña Choez, Jimmy D.
dc.date.accessioned 2015-10-05T10:00:59Z
dc.date.available 2015-10-05T10:00:59Z
dc.date.issued 2012
dc.identifier.bibliographicCitation Torre 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.
dc.identifier.isbn 978-3-642-35292-8 (online)
dc.identifier.isbn 978-3-642-35291-1 (print)
dc.identifier.issn 1865-0929
dc.identifier.uri http://hdl.handle.net/10016/21659
dc.description Proceedings of: IberSPEECH 2012 Conference, Madrid, Spain, November 21-23, 2012.
dc.description.abstract A 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.
dc.description.sponsorship This work has been partially supported by the Spanish Government grants TSI-020110-2009-103 and TEC2011-26807.
dc.format.extent 10
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Springer
dc.relation.ispartofseries Communications in Computer and Information Science
dc.rights © 2012 Springer-Verlag Berlin Heidelberg
dc.subject.other Non-Negative Matrix Factorization
dc.subject.other Kullback-Leibler Divergence
dc.subject.other Sparseness Constraints
dc.subject.other Speech Denoising
dc.subject.other Speech Enhancement
dc.subject.other Automatic Speech Recognition
dc.title Speech Denoising Using Non-Negative Matrix Factorization with Kullback-Leibler Divergence and Sparseness Constraints
dc.type bookPart
dc.type conferenceObject
dc.description.status Publicado
dc.relation.publisherversion http://dx.doi.org/10.1007/978-3-642-35292-8_22
dc.subject.eciencia Telecomunicaciones
dc.identifier.doi 10.1007/978-3-642-35292-8_22
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. TSI-020110-2009-103
dc.relation.projectID Gobierno de España. TEC2011-26807
dc.type.version acceptedVersion
dc.relation.eventdate 2012-11-21
dc.relation.eventnumber 7
dc.relation.eventplace Madrid
dc.relation.eventtitle IberSPEECH 2012 Conference: VII Jornadas en Tecnología del Habla and III Iberian SLTECH Workshop
dc.relation.eventtype proceeding
dc.identifier.publicationfirstpage 207
dc.identifier.publicationlastpage 216
dc.identifier.publicationtitle Advances in Speech and Language Technologies for Iberian Languages: IberSPEECH 2012 Conference, Madrid, Spain, November 21-23, 2012. Proceedings
dc.identifier.publicationvolume 328
dc.identifier.uxxi CC/0000017366
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