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dc.date2016
dc.date.available2016-05-11T20:44:08Z
dc.date.issued2016
dc.identifier.issn1742-6596
dc.identifier.urihttp://dx.doi.org/10.1088/1742-6596/705/1/012037
dc.identifier.urihttp://hdl.handle.net/10784/8373
dc.descriptionA simple but efficient voice activity detector based on the Hilbert transform and a dynamic threshold is presented to be used on the pre-processing of audio signals -- The algorithm to define the dynamic threshold is a modification of a convex combination found in literature -- This scheme allows the detection of prosodic and silence segments on a speech in presence of non-ideal conditions like a spectral overlapped noise -- The present work shows preliminary results over a database built with some political speech -- The tests were performed adding artificial noise to natural noises over the audio signals, and some algorithms are compared -- Results will be extrapolated to the field of adaptive filtering on monophonic signals and the analysis of speech pathologies on futures workseng
dc.formatapplication/pdf
dc.language.isoengspa
dc.publisherIOP Publishingspa
dc.relation.ispartofJournal of Physics: Conference Series; Vol. 705, Núm. 1 (2016); pp.9spa
dc.relation.isversionofhttp://dx.doi.org/10.1088/1742-6596/705/1/012037
dc.sourceJournal of Physics: Conference Series; Vol. 705, Núm. 1 (2016); pp.9spa
dc.subjectTransformada de Hilbert
dc.subjectCancelación de ruidos
dc.subjectSeñal monofónica
dc.titleA simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologieseng
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typearticle
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesseng
dc.description.note20th Argentinean Bioengineering Society Congress, SABI 2015 (XX Congreso Argentino de Bioingeniería y IX Jornadas de Ingeniería Clínica)28–30 October 2015, San Nicolás de los Arroyos, Argentinaeng
dc.subject.lembPROCESAMIENTO DE SEÑALES
dc.subject.lembPROCESAMIENTO DE SEÑALES - TÉCNICAS DIGITALES
dc.subject.lembMEDICIÓN DEL RUIDO
dc.subject.lembFILTROS ADAPTIVOS
dc.subject.lembANÁLISIS DE FOURIER
dc.subject.lembTEORÍA ESPECTRAL (MATEMÁTICAS)
dc.subject.lembANÁLISIS ESPECTRAL
dc.subject.lembPROCESOS DE GAUSS
dc.subject.lembUMBRAL AUDITIVO
dc.type.localArtículospa
dc.subject.keywordSignal processing
dc.subject.keywordSignal processing - Digital techniques
dc.subject.keywordNoise - Measurement
dc.subject.keywordAdaptive filters
dc.subject.keywordFourier analysis
dc.subject.keywordSpectral theory (mathematics)
dc.subject.keywordSpectrum analysis
dc.subject.keywordGaussian processes
dc.subject.keywordAuditory threshold
dc.rights.localAcceso abiertospa
dc.date.accessioned2016-05-11T20:44:08Z
dc.contributor.departmentUniversidad EAFIT. Escuela de Ciencias. Grupo de Investigación Modelado Matemático
dc.rights.licenseCreative Commons Attribution 3.0 licence (CC BY 3.0)eng
dc.contributor.authorOrtiz P., D.spa
dc.contributor.authorVilla, Luisa F.spa
dc.contributor.authorSalazar, Carlosspa
dc.contributor.authorQuintero, O.L.spa
dc.citation.journalTitleJournal of Physics: Conference Seriesspa
dc.citation.volume705
dc.citation.issue1
dc.citation.spage1
dc.citation.epage9
dc.identifier.doi10.1088/1742-6596/705/1/012037
dc.contributor.affiliationMathematical Modeling Research Group, GRIMMAT, School of Sciences, Universidad EAFIT, Medellín, Colombiaspa


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