Use of Paraconsistent Feature Engineering to support the Long Term Feature choice for Speaker Verification

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorAlmeida, Alex M. G. de[UNESP]-
Autor(es): dc.creatorRecco, Claudineia H.-
Autor(es): dc.creatorGuido, Rodrigo C.-
Data de aceite: dc.date.accessioned2025-08-21T22:40:57Z-
Data de disponibilização: dc.date.available2025-08-21T22:40:57Z-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2020-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.32473/flairs.v34i1.128370-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/239854-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/239854-
Descrição: dc.descriptionThe state-of-art models for speech synthesis and voice conversion can generate synthetic speech perceptually indistinguishable from human speech, and speaker verification is crucial to prevent breaches. The building feature that best distinguishes genuine speech between spoof attacks is an open research subject. We used the baseline ASVSpoof2017, Transfer Learning (TL) set, and Symlet and Daubechies Discrete Wavelet Packet Transform (DWPT) for this investigation. To qualitatively assess the features, we used Paraconsistent Feature Engineering (PFE). Our experiments pointed out that for the use of more robust classifiers, the best choice would be the AlexNet method, while in terms of classification regarding the Equal Error Rate metric, the best suggestion would be Daubechies filter support 21. Finally, our findings indicate that Symlet filter support 17 as the most promising feature, which is evidence that PFE is a useful tool and contributes to feature selection.-
Descrição: dc.descriptionDepartament of Computer Science São Paulo State University, Rua Cristóvão Colombo 2265, Jd Nazareth,SP-
Descrição: dc.descriptionDepartament of Computer Science São Paulo State University, Rua Cristóvão Colombo 2265, Jd Nazareth,SP-
Idioma: dc.languageen-
Relação: dc.relationProceedings of the International Florida Artificial Intelligence Research Society Conference, FLAIRS-
???dc.source???: dc.sourceScopus-
Título: dc.titleUse of Paraconsistent Feature Engineering to support the Long Term Feature choice for Speaker Verification-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

Não existem arquivos associados a este item.