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Feature extraction based on the high-pass filtering of audio signals for Acoustic Event Classification

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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.authorLudeña Choez, Jimmy D.
dc.contributor.authorGallardo Antolín, Ascensión
dc.date.accessioned2015-09-11T10:19:15Z
dc.date.available2017-03-01T23:00:08Z
dc.date.issued2015-03
dc.description.abstractIn this paper, we propose a new front-end for Acoustic Event Classification tasks ( AEC). First, we study the spectral characteristics of different acoustic events in comparison with the structure of speech spectra. Second, from the findings of this study, we propose a new parameterization for AEC, which is an extension of the conventional Mel-Frequency Cepstral Coefficients ( MFCC) and is based on the high pass filtering of the acoustic event signal. The proposed front-end have been tested in clean and noisy conditions and compared to the conventional MFCC in an AEC task. Results support the fact that the high pass filtering of the audio signal is, in general terms, beneficial for the system, showing that the removal of frequencies below 100-275 Hz in the feature extraction process in clean conditions and below 400-500 Hz in noisy conditions, improves significantly the performance of the system with respect to the baseline.en
dc.description.sponsorshipThis work has been partially supported by the Spanish Government grants IPT-120000-2010-24 and TEC2011-26807. Financial support from the Fundación Carolina and Universidad Católica San Pablo, Arequipa.en
dc.description.statusPublicadoes
dc.format.extent19
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationComputer Speech & Language (2015). 30(1), 32-42.en
dc.identifier.doi10.1016/j.csl.2014.04.001
dc.identifier.issn0885-2308
dc.identifier.publicationfirstpage32
dc.identifier.publicationissue1
dc.identifier.publicationlastpage42
dc.identifier.publicationtitleComputer speech and languageen
dc.identifier.publicationvolume30
dc.identifier.urihttps://hdl.handle.net/10016/21548
dc.identifier.uxxiAR/0000015928
dc.language.isoengen
dc.publisherElsevieren
dc.relation.projectIDGobierno de España. TEC2011-26807es
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.csl.2014.04.001es
dc.rights© 2014 Elsevier Ltd.
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherAcoustic Event Classificationen
dc.subject.otherHigh-pass filteringen
dc.subject.otherAuditory filterbanken
dc.titleFeature extraction based on the high-pass filtering of audio signals for Acoustic Event Classificationen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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