Maximum a Posteriori Binary Mask Estimation for Underdetermined Source Separation Using Smoothed Posteriors

Sound source separation has become a topic of intensive research in the last years. The research effort has been specially relevant for the underdetermined case, where a considerable number of sparse methods working in the time-frequency (T-F) domain have appeared. In this context, although binary m...

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Detalles Bibliográficos
Autores: Cobos Serrano, Máximo, López Monfort, José Javier|||0000-0001-6884-5577
Tipo de recurso: artículo
Fecha de publicación:2012
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/55961
Acceso en línea:https://riunet.upv.es/handle/10251/55961
Access Level:acceso abierto
Palabra clave:Direction of arrival estimation
Estimation
Histograms
Indexes
Speech
Speech processing
Time frequency analysis
TEORIA DE LA SEÑAL Y COMUNICACIONES
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spelling Maximum a Posteriori Binary Mask Estimation for Underdetermined Source Separation Using Smoothed PosteriorsCobos Serrano, MáximoLópez Monfort, José Javier|||0000-0001-6884-5577Direction of arrival estimationEstimationHistogramsIndexesSpeechSpeech processingTime frequency analysisTEORIA DE LA SEÑAL Y COMUNICACIONESSound source separation has become a topic of intensive research in the last years. The research effort has been specially relevant for the underdetermined case, where a considerable number of sparse methods working in the time-frequency (T-F) domain have appeared. In this context, although binary masking seems to be a preferred choice for source demixing, the estimated masks differ substantially from the ideal ones. This paper proposes a maximum a posteriori (MAP) framework for binary mask estimation. To this end, class-conditional source probabilities according to the observed mixing parameters are modeled via ratios of dependent Cauchy distributions while source priors are iteratively calculated from the observed histograms. Moreover, spatially smoothed posteriors in the T-F domain are proposed to avoid noisy estimates, showing that the estimated masks are closer to the ideal ones in terms of objective performance measures.This work was supported by the Spanish Ministry of Science and Innovation under project TEC2009-14414-C03-01. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Jingdong Chen.Institute of Electrical and Electronics Engineers (IEEE)Escuela Técnica Superior de Ingeniería de TelecomunicaciónDepartamento de ComunicacionesInstituto Universitario de Telecomunicación y Aplicaciones MultimediaMinisterio de Ciencia e InnovaciónRepositorio Institucional de la Universitat Politècnica de València Riunet20122012-09-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://riunet.upv.es/handle/10251/55961reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengMinisterio de Ciencia e Innovación http://dx.doi.org/10.13039/501100004837 TEC2009-14414-C03-01 Procesado De Sonido Para Entornos Emergentes De Comunicacionopen accesshttp://purl.org/coar/access_right/c_abf2Reserva de todos los derechoshttp://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/559612026-06-13T07:49:27Z
dc.title.none.fl_str_mv Maximum a Posteriori Binary Mask Estimation for Underdetermined Source Separation Using Smoothed Posteriors
title Maximum a Posteriori Binary Mask Estimation for Underdetermined Source Separation Using Smoothed Posteriors
spellingShingle Maximum a Posteriori Binary Mask Estimation for Underdetermined Source Separation Using Smoothed Posteriors
Cobos Serrano, Máximo
Direction of arrival estimation
Estimation
Histograms
Indexes
Speech
Speech processing
Time frequency analysis
TEORIA DE LA SEÑAL Y COMUNICACIONES
title_short Maximum a Posteriori Binary Mask Estimation for Underdetermined Source Separation Using Smoothed Posteriors
title_full Maximum a Posteriori Binary Mask Estimation for Underdetermined Source Separation Using Smoothed Posteriors
title_fullStr Maximum a Posteriori Binary Mask Estimation for Underdetermined Source Separation Using Smoothed Posteriors
title_full_unstemmed Maximum a Posteriori Binary Mask Estimation for Underdetermined Source Separation Using Smoothed Posteriors
title_sort Maximum a Posteriori Binary Mask Estimation for Underdetermined Source Separation Using Smoothed Posteriors
dc.creator.none.fl_str_mv Cobos Serrano, Máximo
López Monfort, José Javier|||0000-0001-6884-5577
author Cobos Serrano, Máximo
author_facet Cobos Serrano, Máximo
López Monfort, José Javier|||0000-0001-6884-5577
author_role author
author2 López Monfort, José Javier|||0000-0001-6884-5577
author2_role author
dc.contributor.none.fl_str_mv Escuela Técnica Superior de Ingeniería de Telecomunicación
Departamento de Comunicaciones
Instituto Universitario de Telecomunicación y Aplicaciones Multimedia
Ministerio de Ciencia e Innovación
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Direction of arrival estimation
Estimation
Histograms
Indexes
Speech
Speech processing
Time frequency analysis
TEORIA DE LA SEÑAL Y COMUNICACIONES
topic Direction of arrival estimation
Estimation
Histograms
Indexes
Speech
Speech processing
Time frequency analysis
TEORIA DE LA SEÑAL Y COMUNICACIONES
description Sound source separation has become a topic of intensive research in the last years. The research effort has been specially relevant for the underdetermined case, where a considerable number of sparse methods working in the time-frequency (T-F) domain have appeared. In this context, although binary masking seems to be a preferred choice for source demixing, the estimated masks differ substantially from the ideal ones. This paper proposes a maximum a posteriori (MAP) framework for binary mask estimation. To this end, class-conditional source probabilities according to the observed mixing parameters are modeled via ratios of dependent Cauchy distributions while source priors are iteratively calculated from the observed histograms. Moreover, spatially smoothed posteriors in the T-F domain are proposed to avoid noisy estimates, showing that the estimated masks are closer to the ideal ones in terms of objective performance measures.
publishDate 2012
dc.date.none.fl_str_mv 2012
2012-09-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/55961
url https://riunet.upv.es/handle/10251/55961
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Ministerio de Ciencia e Innovación http://dx.doi.org/10.13039/501100004837 TEC2009-14414-C03-01 Procesado De Sonido Para Entornos Emergentes De Comunicacion
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers (IEEE)
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers (IEEE)
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300719

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