HMM modeling of additive noise in the western languages context

Bibliographic Details
Main Author: Lima, C. S.
Publication Date: 2003
Other Authors: Oliveira, Jorge F.
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/1822/2053
Summary: This paper is concerned to the noisy speech HMM modelling when the noise is additive, speech independent and the spectral analysis is based on sub-bands. The internal distributions of the noisy speech HMM’s were derived when Gaussian mixture density distributions for clean speech HMM modelling are used, and the noise is normally distributed and additive in the time domain. In these circumstances it is showed that the HMM noisy speech distributions are not Gaussians, however, fitting these distributions as a Gaussian mixture, only a little bit of loss in performance was obtained at very low signal to noise ratios, when compared with the case where the real distributions were computed using Monte Carlo methods.
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spelling HMM modeling of additive noise in the western languages contextHMM modellingModel adaptationThis paper is concerned to the noisy speech HMM modelling when the noise is additive, speech independent and the spectral analysis is based on sub-bands. The internal distributions of the noisy speech HMM’s were derived when Gaussian mixture density distributions for clean speech HMM modelling are used, and the noise is normally distributed and additive in the time domain. In these circumstances it is showed that the HMM noisy speech distributions are not Gaussians, however, fitting these distributions as a Gaussian mixture, only a little bit of loss in performance was obtained at very low signal to noise ratios, when compared with the case where the real distributions were computed using Monte Carlo methods.Universidade do MinhoLima, C. S.Oliveira, Jorge F.2003-122003-12-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/2053engINTERNATIONAL WORKSHOP ON MODELS AND ANALYSIS OF VOCAL EMISSIONS FOR BIOMEDICAL APPLICATIONS (MAVEBA), 3, Firenze, 2003.info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T06:57:12Zoai:repositorium.sdum.uminho.pt:1822/2053Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:10:00.275947Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv HMM modeling of additive noise in the western languages context
title HMM modeling of additive noise in the western languages context
spellingShingle HMM modeling of additive noise in the western languages context
Lima, C. S.
HMM modelling
Model adaptation
title_short HMM modeling of additive noise in the western languages context
title_full HMM modeling of additive noise in the western languages context
title_fullStr HMM modeling of additive noise in the western languages context
title_full_unstemmed HMM modeling of additive noise in the western languages context
title_sort HMM modeling of additive noise in the western languages context
author Lima, C. S.
author_facet Lima, C. S.
Oliveira, Jorge F.
author_role author
author2 Oliveira, Jorge F.
author2_role author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Lima, C. S.
Oliveira, Jorge F.
dc.subject.por.fl_str_mv HMM modelling
Model adaptation
topic HMM modelling
Model adaptation
description This paper is concerned to the noisy speech HMM modelling when the noise is additive, speech independent and the spectral analysis is based on sub-bands. The internal distributions of the noisy speech HMM’s were derived when Gaussian mixture density distributions for clean speech HMM modelling are used, and the noise is normally distributed and additive in the time domain. In these circumstances it is showed that the HMM noisy speech distributions are not Gaussians, however, fitting these distributions as a Gaussian mixture, only a little bit of loss in performance was obtained at very low signal to noise ratios, when compared with the case where the real distributions were computed using Monte Carlo methods.
publishDate 2003
dc.date.none.fl_str_mv 2003-12
2003-12-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/2053
url http://hdl.handle.net/1822/2053
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv INTERNATIONAL WORKSHOP ON MODELS AND ANALYSIS OF VOCAL EMISSIONS FOR BIOMEDICAL APPLICATIONS (MAVEBA), 3, Firenze, 2003.
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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