Publication
Comparative Analysis of Windows for Speech Emotion Recognition Using CNN
| dc.contributor.author | Teixeira, Felipe | |
| dc.contributor.author | Soares, Salviano Pinto | |
| dc.contributor.author | Abreu, J.L. Pio | |
| dc.contributor.author | Oliveira, Paulo M. | |
| dc.contributor.author | Teixeira, João Paulo | |
| dc.date.accessioned | 2024-10-08T09:12:50Z | |
| dc.date.available | 2024-10-08T09:12:50Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | The paper presents the comparison of accuracy in the Speech Emotion Recognition task using the Hamming and Hanning windows for framing the speech and determining the spectrogram to be used as input of a convolutional neural network. The detection of between 4 and 10 emotional states was tested for both windows. The results show significant differences in accuracy between the two window types and provide valuable insights for the development of more efficient emotional state detection systems. The best accuracy between 4 and 10 emotions was 64.1% (4 emotions), 57.8% (5 emotions), 59.8% (6 emotions), 48.4% (7 emotions), 47.8% (8 emotions), 51.4% (9 emotions), and 45.9% (10 emotions). These accuracy is at the state-of-the art level. | pt_PT |
| dc.description.sponsorship | This research was funded by the European Regional Development Fund (ERDF) via the Regional Operational Program North 2020, GreenHealth- Digital strategies in biological assets to improve well-being and promote green health, Norte-01-0145-FEDER-000042; Foundation for Science and Technology (FCT, Portugal) support from national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021). The authors are grateful for financial support from UTAD. The authors would also like to thank Jo˜ao Mendes for his collaboration throughout the work. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Teixeira, Felipe L.; Soares, Salviano Pinto; Abreu, J.L. Pio; Oliveira, Paulo M.; Teixeira, João P. (2024). Comparative Analysis of Windows for Speech Emotion Recognition Using CNN. In 3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023). Cham: Springer Nature, Vol. 1, p. 233–248. ISBN 978-3-031-53024-1. | pt_PT |
| dc.identifier.doi | 10.1007/978-3-031-53025-8_17 | pt_PT |
| dc.identifier.isbn | 978-3-031-53024-1 | |
| dc.identifier.isbn | 978-3-031-53025-8 | |
| dc.identifier.uri | http://hdl.handle.net/10198/30344 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | 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 | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Speech Emotion Recognition | pt_PT |
| dc.subject | Hamming | pt_PT |
| dc.subject | Hanning | pt_PT |
| dc.subject | CNN | pt_PT |
| dc.title | Comparative Analysis of Windows for Speech Emotion Recognition Using CNN | pt_PT |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| 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 | |
| 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 | 248 | pt_PT |
| oaire.citation.startPage | 233 | 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.familyName | Teixeira | |
| person.givenName | Felipe | |
| person.givenName | João Paulo | |
| person.identifier | 663194 | |
| person.identifier.ciencia-id | 0E17-62FB-AA17 | |
| 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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