Logo do repositório
 
Publicação

Speaker recognitionin door access control system

dc.contributor.authorManfron, E.
dc.contributor.authorTeixeira, João Paulo
dc.contributor.authorMineto, R.
dc.date.accessioned2026-05-18T11:25:55Z
dc.date.available2026-05-18T11:25:55Z
dc.date.issued2023
dc.description.abstractIn this paper, we explore the potential of speaker recognition technology as a biometric authentication method for access control systems. We focus on the development and evaluation of two machine learning models, the Gaussian Mixture Model (GMM) and Multilayer Perceptron (MLP), for speaker identification. Our research presents a review of speaker recognition literature, followed by a detailed methodology for constructing and training the GMM and MLP models on a specific dataset. Experimental results highlight the performance of these models in terms of accuracy and efficiency. This study contributes to the application of GMM and MLP models for speaker recognition-based access control systems, serving as a resource for future research and development in secure and effective access control solutions.por
dc.identifier.citationManfron, E.; Teixeira, João Paulo; Mineto, R. (2023). Speaker recognition in door access control system. In the third Symposium of Applied Science for Young Researchers - SASYR 2023.
dc.identifier.urihttp://hdl.handle.net/10198/36704
dc.language.isoeng
dc.peerreviewedyes
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleSpeaker recognitionin door access control systempor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferenceDate2023
oaire.citation.titlethe third Symposium of Applied Science for Young Researchers - SASYR 2023
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameTeixeira
person.givenNameJoão Paulo
person.identifier663194
person.identifier.ciencia-id4F15-B322-59B4
person.identifier.orcid0000-0002-6679-5702
person.identifier.ridN-6576-2013
person.identifier.scopus-author-id57069567500
relation.isAuthorOfPublication33f4af65-7ddf-46f0-8b44-a7470a8ba2bf
relation.isAuthorOfPublication.latestForDiscovery33f4af65-7ddf-46f0-8b44-a7470a8ba2bf

Ficheiros

Principais
A mostrar 1 - 1 de 1
A carregar...
Miniatura
Nome:
GMM_and_MPL_SASYR_Paper.pdf
Tamanho:
2 MB
Formato:
Adobe Portable Document Format
Licença
A mostrar 1 - 1 de 1
Miniatura indisponível
Nome:
license.txt
Tamanho:
1.75 KB
Formato:
Item-specific license agreed upon to submission
Descrição: