A comparative study between recent wavelet nonthresholding methods and the well-established spectral subtractive and statistical-model-based algorithms for speech enhancement under real noisy conditions

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorState University of Mato Grosso-
Autor(es): dc.contributorSaõ Paulo State University-
Autor(es): dc.contributorState University of Mato Grosso Do sul-
Autor(es): dc.creatorDe Abreu, Caio C. E.-
Autor(es): dc.creatorTravassos, Natalia C. L.-
Autor(es): dc.creatorDuarte, Marco A. Q.-
Autor(es): dc.creatorVillarreal, Francisco-
Data de aceite: dc.date.accessioned2022-08-04T22:06:19Z-
Data de disponibilização: dc.date.available2022-08-04T22:06:19Z-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2017-03-08-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/INDUSCON.2016.7874494-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/220818-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/220818-
Descrição: dc.descriptionIn this paper, a comparative study between current wavelet nonthresholding methods for speech enhancement and the well-established spectral subtractive and statistical-model-based algorithms is performed. The development and evaluation of speech enhancement methods is essential in many branches of telecommunications and entertainment industry. Two classes of speech enhancement methods encompassing both, DFT and wavelet based methods, are evaluated and faced with the current wavelet nonthresholding schemes. Objective analysis taking into account various real noise environments are presented. Questions about wavelet thresholding performance on real noisy environments are discussed. Objective evaluations considering SNR improvement, correlation among original and enhanced sentences and PESQ scores shown that nonthresholding schemes overcome totally the wavelet thresholding methods in PESQ scores, besides performing equally well in noise suppression. A second objective is the identification, among the considered methods, of the more suitable to certain kind of real noisy conditions.-
Descrição: dc.descriptionDepartment of Computing State University of Mato Grosso-
Descrição: dc.descriptionDepartment of Electrical Engineering Saõ Paulo State University-
Descrição: dc.descriptionDepartment of Mathematics State University of Mato Grosso Do sul-
Descrição: dc.descriptionDepartment of Mathematics Saõ Paulo State University-
Idioma: dc.languageen-
Relação: dc.relation2016 12th IEEE International Conference on Industry Applications, INDUSCON 2016-
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Título: dc.titleA comparative study between recent wavelet nonthresholding methods and the well-established spectral subtractive and statistical-model-based algorithms for speech enhancement under real noisy conditions-
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