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...
- 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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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 |
bitstream.checksum.fl_str_mv |
4ce1f12b898fce8392c0b2f5059b2432 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 |
repository.name.fl_str_mv |
Repositorio Institucional Universidad EAFIT |
repository.mail.fl_str_mv |
repositorio@eafit.edu.co |
_version_ |
1814110515579846656 |