A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies

A 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 th...

Full description

Autores:
Ortiz P., D.
Villa, Luisa F.
Salazar, Carlos
Quintero, O.L.
Ortiz P., D.
Villa, Luisa F.
Salazar, Carlos
Quintero, O.L.
Tipo de recurso:
Fecha de publicación:
2016
Institución:
Universidad EAFIT
Repositorio:
Repositorio EAFIT
Idioma:
eng
OAI Identifier:
oai:repository.eafit.edu.co:10784/8373
Acceso en línea:
http://hdl.handle.net/10784/8373
Palabra clave:
Transformada de Hilbert
Cancelación de ruidos
Señal monofónica
PROCESAMIENTO DE SEÑALES
PROCESAMIENTO DE SEÑALES - TÉCNICAS DIGITALES
MEDICIÓN DEL RUIDO
FILTROS ADAPTIVOS
ANÁLISIS DE FOURIER
TEORÍA ESPECTRAL (MATEMÁTICAS)
ANÁLISIS ESPECTRAL
PROCESOS DE GAUSS
UMBRAL AUDITIVO
Signal processing
Signal processing - Digital techniques
Noise - Measurement
Adaptive filters
Fourier analysis
Spectral theory (mathematics)
Spectrum analysis
Gaussian processes
Auditory threshold
Signal processing
Signal processing - Digital techniques
Noise - Measurement
Adaptive filters
Fourier analysis
Spectral theory (mathematics)
Spectrum analysis
Gaussian processes
Auditory threshold
Transformada de Hilbert
Cancelación de ruidos
Señal monofónica
Rights
License
Acceso abierto
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oai_identifier_str oai:repository.eafit.edu.co:10784/8373
network_acronym_str REPOEAFIT2
network_name_str Repositorio EAFIT
repository_id_str
spelling 20162016-05-11T20:44:08Z20162016-05-11T20:44:08Z1742-6596http://hdl.handle.net/10784/837310.1088/1742-6596/705/1/012037A 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 works20th 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, Argentinaapplication/pdfengIOP PublishingJournal of Physics: Conference Series; Vol. 705, Núm. 1 (2016); pp.9http://dx.doi.org/10.1088/1742-6596/705/1/012037http://dx.doi.org/10.1088/1742-6596/705/1/012037Journal of Physics: Conference SeriesTransformada de HilbertCancelación de ruidosSeñal monofónicaPROCESAMIENTO DE SEÑALESPROCESAMIENTO DE SEÑALES - TÉCNICAS DIGITALESMEDICIÓN DEL RUIDOFILTROS ADAPTIVOSANÁLISIS DE FOURIERTEORÍA ESPECTRAL (MATEMÁTICAS)ANÁLISIS ESPECTRALPROCESOS DE GAUSSUMBRAL AUDITIVOSignal processingSignal processing - Digital techniquesNoise - MeasurementAdaptive filtersFourier analysisSpectral theory (mathematics)Spectrum analysisGaussian processesAuditory thresholdSignal processingSignal processing - Digital techniquesNoise - MeasurementAdaptive filtersFourier analysisSpectral theory (mathematics)Spectrum analysisGaussian processesAuditory thresholdTransformada de HilbertCancelación de ruidosSeñal monofónicaA simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologiesinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionarticlearticleinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionpublishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Acceso abiertoCreative Commons Attribution 3.0 licence (CC BY 3.0)http://purl.org/coar/access_right/c_abf2Universidad EAFIT. Escuela de Cienciasdpuerta1@eafit.edu.cooquinte1@eafit.edu.coOrtiz P., D.Villa, Luisa F.Salazar, CarlosQuintero, O.L.Ortiz P., D.Villa, Luisa F.Salazar, CarlosQuintero, O.L.Mathematical Modeling Research Group, GRIMMAT, School of Sciences, Universidad EAFIT, Medellín, ColombiaModelado MatemáticoJournal of Physics: Conference Series705119ORIGINALJPCS_705_1_012037.pdfJPCS_705_1_012037.pdfTexto completoapplication/pdf1370176https://repository.eafit.edu.co/bitstreams/36064881-de62-4627-8fcc-8760d808356a/download4ce1f12b898fce8392c0b2f5059b2432MD5110784/8373oai:repository.eafit.edu.co:10784/83732022-08-26 09:40:23.634open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.co
dc.title.eng.fl_str_mv A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies
title A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies
spellingShingle A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies
Transformada de Hilbert
Cancelación de ruidos
Señal monofónica
PROCESAMIENTO DE SEÑALES
PROCESAMIENTO DE SEÑALES - TÉCNICAS DIGITALES
MEDICIÓN DEL RUIDO
FILTROS ADAPTIVOS
ANÁLISIS DE FOURIER
TEORÍA ESPECTRAL (MATEMÁTICAS)
ANÁLISIS ESPECTRAL
PROCESOS DE GAUSS
UMBRAL AUDITIVO
Signal processing
Signal processing - Digital techniques
Noise - Measurement
Adaptive filters
Fourier analysis
Spectral theory (mathematics)
Spectrum analysis
Gaussian processes
Auditory threshold
Signal processing
Signal processing - Digital techniques
Noise - Measurement
Adaptive filters
Fourier analysis
Spectral theory (mathematics)
Spectrum analysis
Gaussian processes
Auditory threshold
Transformada de Hilbert
Cancelación de ruidos
Señal monofónica
title_short A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies
title_full A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies
title_fullStr A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies
title_full_unstemmed A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies
title_sort A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies
dc.creator.fl_str_mv Ortiz P., D.
Villa, Luisa F.
Salazar, Carlos
Quintero, O.L.
Ortiz P., D.
Villa, Luisa F.
Salazar, Carlos
Quintero, O.L.
dc.contributor.department.spa.fl_str_mv Universidad EAFIT. Escuela de Ciencias
dc.contributor.eafitauthor.none.fl_str_mv dpuerta1@eafit.edu.co
oquinte1@eafit.edu.co
dc.contributor.author.spa.fl_str_mv Ortiz P., D.
Villa, Luisa F.
Salazar, Carlos
Quintero, O.L.
dc.contributor.author.none.fl_str_mv Ortiz P., D.
Villa, Luisa F.
Salazar, Carlos
Quintero, O.L.
dc.contributor.affiliation.spa.fl_str_mv Mathematical Modeling Research Group, GRIMMAT, School of Sciences, Universidad EAFIT, Medellín, Colombia
dc.contributor.researchgroup.spa.fl_str_mv Modelado Matemático
dc.subject.none.fl_str_mv Transformada de Hilbert
Cancelación de ruidos
Señal monofónica
topic Transformada de Hilbert
Cancelación de ruidos
Señal monofónica
PROCESAMIENTO DE SEÑALES
PROCESAMIENTO DE SEÑALES - TÉCNICAS DIGITALES
MEDICIÓN DEL RUIDO
FILTROS ADAPTIVOS
ANÁLISIS DE FOURIER
TEORÍA ESPECTRAL (MATEMÁTICAS)
ANÁLISIS ESPECTRAL
PROCESOS DE GAUSS
UMBRAL AUDITIVO
Signal processing
Signal processing - Digital techniques
Noise - Measurement
Adaptive filters
Fourier analysis
Spectral theory (mathematics)
Spectrum analysis
Gaussian processes
Auditory threshold
Signal processing
Signal processing - Digital techniques
Noise - Measurement
Adaptive filters
Fourier analysis
Spectral theory (mathematics)
Spectrum analysis
Gaussian processes
Auditory threshold
Transformada de Hilbert
Cancelación de ruidos
Señal monofónica
dc.subject.lemb.none.fl_str_mv PROCESAMIENTO DE SEÑALES
PROCESAMIENTO DE SEÑALES - TÉCNICAS DIGITALES
MEDICIÓN DEL RUIDO
FILTROS ADAPTIVOS
ANÁLISIS DE FOURIER
TEORÍA ESPECTRAL (MATEMÁTICAS)
ANÁLISIS ESPECTRAL
PROCESOS DE GAUSS
UMBRAL AUDITIVO
dc.subject.keyword.none.fl_str_mv Signal processing
Signal processing - Digital techniques
Noise - Measurement
Adaptive filters
Fourier analysis
Spectral theory (mathematics)
Spectrum analysis
Gaussian processes
Auditory threshold
dc.subject.keyword.eng.fl_str_mv Signal processing
Signal processing - Digital techniques
Noise - Measurement
Adaptive filters
Fourier analysis
Spectral theory (mathematics)
Spectrum analysis
Gaussian processes
Auditory threshold
dc.subject.keyword.spa.fl_str_mv Transformada de Hilbert
Cancelación de ruidos
Señal monofónica
description A 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 works
publishDate 2016
dc.date.available.none.fl_str_mv 2016-05-11T20:44:08Z
dc.date.issued.none.fl_str_mv 2016
dc.date.accessioned.none.fl_str_mv 2016-05-11T20:44:08Z
dc.date.none.fl_str_mv 2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
article
dc.type.eng.fl_str_mv article
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
publishedVersion
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.local.spa.fl_str_mv Artículo
status_str publishedVersion
dc.identifier.issn.none.fl_str_mv 1742-6596
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10784/8373
dc.identifier.doi.none.fl_str_mv 10.1088/1742-6596/705/1/012037
identifier_str_mv 1742-6596
10.1088/1742-6596/705/1/012037
url http://hdl.handle.net/10784/8373
dc.language.iso.eng.fl_str_mv eng
language eng
dc.relation.ispartof.spa.fl_str_mv Journal of Physics: Conference Series; Vol. 705, Núm. 1 (2016); pp.9
dc.relation.isversionof.none.fl_str_mv http://dx.doi.org/10.1088/1742-6596/705/1/012037
dc.relation.uri.none.fl_str_mv http://dx.doi.org/10.1088/1742-6596/705/1/012037
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.local.spa.fl_str_mv Acceso abierto
dc.rights.license.eng.fl_str_mv Creative Commons Attribution 3.0 licence (CC BY 3.0)
rights_invalid_str_mv Acceso abierto
Creative Commons Attribution 3.0 licence (CC BY 3.0)
http://purl.org/coar/access_right/c_abf2
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IOP Publishing
publisher.none.fl_str_mv IOP Publishing
dc.source.none.fl_str_mv Journal of Physics: Conference Series
institution Universidad EAFIT
bitstream.url.fl_str_mv https://repository.eafit.edu.co/bitstreams/36064881-de62-4627-8fcc-8760d808356a/download
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repository.name.fl_str_mv Repositorio Institucional Universidad EAFIT
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