A bioinspired spectro-temporal domain for sound denoising

Autores
Martínez, César E.; Goddard, J.; Di Persia, L.; Milone, Diego H.; Rufiner, Hugo Leonardo
Año de publicación
2016
Idioma
español castellano
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The representation of sound signals at the cochlea and au- ditory cortical level has been studied as an alternative to classical anal- ysis methods. In this work, we put forward a recently proposed feature extraction method called approximate auditory cortical representation, based on an approximation to the statistics of discharge patterns at the primary auditory cortex. The approach here proposed estimates a non- negative sparse coding with a combined dictionary of atoms calculated from clean signal and noise. The denoising is carried out on noisy signals by the reconstruction of the signal discarding the atoms corresponding to the noise. Results on synthetic and real data show that the proposed method improves the quality of the signals, mainly under severe degra- dation. This communication corresponds to a journal paper published in 2015 in DSP (Elsevier).
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
Materia
Ciencias Informáticas
approximate auditory cortical representation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-sa/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/57027

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spelling A bioinspired spectro-temporal domain for sound denoisingMartínez, César E.Goddard, J.Di Persia, L.Milone, Diego H.Rufiner, Hugo LeonardoCiencias Informáticasapproximate auditory cortical representationThe representation of sound signals at the cochlea and au- ditory cortical level has been studied as an alternative to classical anal- ysis methods. In this work, we put forward a recently proposed feature extraction method called approximate auditory cortical representation, based on an approximation to the statistics of discharge patterns at the primary auditory cortex. The approach here proposed estimates a non- negative sparse coding with a combined dictionary of atoms calculated from clean signal and noise. The denoising is carried out on noisy signals by the reconstruction of the signal discarding the atoms corresponding to the noise. Results on synthetic and real data show that the proposed method improves the quality of the signals, mainly under severe degra- dation. This communication corresponds to a journal paper published in 2015 in DSP (Elsevier).Sociedad Argentina de Informática e Investigación Operativa (SADIO)2016-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf139-141http://sedici.unlp.edu.ar/handle/10915/57027spainfo:eu-repo/semantics/altIdentifier/url/http://45jaiio.sadio.org.ar/sites/default/files/ASAI-22_0.pdfinfo:eu-repo/semantics/altIdentifier/issn/2451-7585info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-sa/3.0/Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:38:52Zoai:sedici.unlp.edu.ar:10915/57027Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:38:52.398SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A bioinspired spectro-temporal domain for sound denoising
title A bioinspired spectro-temporal domain for sound denoising
spellingShingle A bioinspired spectro-temporal domain for sound denoising
Martínez, César E.
Ciencias Informáticas
approximate auditory cortical representation
title_short A bioinspired spectro-temporal domain for sound denoising
title_full A bioinspired spectro-temporal domain for sound denoising
title_fullStr A bioinspired spectro-temporal domain for sound denoising
title_full_unstemmed A bioinspired spectro-temporal domain for sound denoising
title_sort A bioinspired spectro-temporal domain for sound denoising
dc.creator.none.fl_str_mv Martínez, César E.
Goddard, J.
Di Persia, L.
Milone, Diego H.
Rufiner, Hugo Leonardo
author Martínez, César E.
author_facet Martínez, César E.
Goddard, J.
Di Persia, L.
Milone, Diego H.
Rufiner, Hugo Leonardo
author_role author
author2 Goddard, J.
Di Persia, L.
Milone, Diego H.
Rufiner, Hugo Leonardo
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
approximate auditory cortical representation
topic Ciencias Informáticas
approximate auditory cortical representation
dc.description.none.fl_txt_mv The representation of sound signals at the cochlea and au- ditory cortical level has been studied as an alternative to classical anal- ysis methods. In this work, we put forward a recently proposed feature extraction method called approximate auditory cortical representation, based on an approximation to the statistics of discharge patterns at the primary auditory cortex. The approach here proposed estimates a non- negative sparse coding with a combined dictionary of atoms calculated from clean signal and noise. The denoising is carried out on noisy signals by the reconstruction of the signal discarding the atoms corresponding to the noise. Results on synthetic and real data show that the proposed method improves the quality of the signals, mainly under severe degra- dation. This communication corresponds to a journal paper published in 2015 in DSP (Elsevier).
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
description The representation of sound signals at the cochlea and au- ditory cortical level has been studied as an alternative to classical anal- ysis methods. In this work, we put forward a recently proposed feature extraction method called approximate auditory cortical representation, based on an approximation to the statistics of discharge patterns at the primary auditory cortex. The approach here proposed estimates a non- negative sparse coding with a combined dictionary of atoms calculated from clean signal and noise. The denoising is carried out on noisy signals by the reconstruction of the signal discarding the atoms corresponding to the noise. Results on synthetic and real data show that the proposed method improves the quality of the signals, mainly under severe degra- dation. This communication corresponds to a journal paper published in 2015 in DSP (Elsevier).
publishDate 2016
dc.date.none.fl_str_mv 2016-09
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dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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