Publicação
Deep Learning and Machine Learning Techniques Applied to Speaker Identification on Small Datasets
| dc.contributor.author | Manfron, Enrico | |
| dc.contributor.author | Teixeira, João Paulo | |
| dc.contributor.author | Minetto, Rodrigo | |
| dc.date.accessioned | 2024-10-08T14:32:17Z | |
| dc.date.available | 2024-10-08T14:32:17Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | In this study, we explore the capabilities of speaker recognition technology for biometric authentication developing speaker recognition-based access control systems and serving as a resource for future research and improvements in secure and efficient speaker identification solutions. We focused on developing and evaluating machine learning and deep learning models for speaker identification. The models were trained and tested on private datasets with 32 speakers and public datasets with 1251 to 6112 speakers. The Gaussian Mixture Model performed well with our private datasets, with 93,10%, and 95% accuracy in correctly identifying the speakers. The Multilayer Perceptron achieved a peak accuracy of 93.33% on the Framed Trim private dataset. The VGGM model, after initial training on larger datasets, achieved an accuracy of 90.34% and 98.33% on our private datasets. At last, the model ResNet50 slightly outperformed the other models on two versions of our private dataset, achieving accuracies of 97.93% and 100%. | pt_PT |
| dc.description.sponsorship | The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021). | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Manfron, Enrico; Teixeira, João Paulo; Minetto, Rodrigo (2024). Deep Learning and Machine Learning Techniques Applied to Speaker Identification on Small Datasets. In 3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023). Cham: Springer Nature, Vol. 2, p. 195–210. ISBN 978-3-031-53035-7 | pt_PT |
| dc.identifier.doi | 10.1007/978-3-031-53036-4_14 | pt_PT |
| dc.identifier.isbn | 978-3-031-53035-7 | |
| dc.identifier.isbn | 978-3-031-53036-4 | |
| dc.identifier.uri | http://hdl.handle.net/10198/30380 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Springer Nature | pt_PT |
| dc.relation | Research Centre in Digitalization and Intelligent Robotics | |
| dc.relation | Research Centre in Digitalization and Intelligent Robotics | |
| dc.relation | Associate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020 | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Speaker Identification | pt_PT |
| dc.subject | Convolutional Neural Network | pt_PT |
| dc.subject | Deep Learning | pt_PT |
| dc.title | Deep Learning and Machine Learning Techniques Applied to Speaker Identification on Small Datasets | pt_PT |
| dc.type | conference paper | |
| dspace.entity.type | Publication | |
| oaire.awardNumber | UIDB/05757/2020 | |
| oaire.awardNumber | UIDP/05757/2020 | |
| oaire.awardNumber | LA/P/0007/2020 | |
| oaire.awardTitle | Research Centre in Digitalization and Intelligent Robotics | |
| oaire.awardTitle | Research Centre in Digitalization and Intelligent Robotics | |
| oaire.awardTitle | Associate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020 | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT | |
| oaire.citation.endPage | 210 | pt_PT |
| oaire.citation.startPage | 195 | pt_PT |
| oaire.citation.title | 3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023) | pt_PT |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| person.familyName | Teixeira | |
| person.givenName | João Paulo | |
| person.identifier | 663194 | |
| person.identifier.ciencia-id | 4F15-B322-59B4 | |
| person.identifier.orcid | 0000-0002-6679-5702 | |
| person.identifier.rid | N-6576-2013 | |
| person.identifier.scopus-author-id | 57069567500 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | restrictedAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
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