An Evaluation of Physiological Public Datasets for Emotion Recognition Systems

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Acknowledgment. A. Mendoza, A. Cuno, N. Condori-Fernandez and W. Ramos acknowledge financial support from the “Proyecto Concytec - Banco Mundial, Mejo-ramiento y Ampliación de los Servicios del Sistema Nacional de Ciencia Tecnología e Innovación Tecnológica” 8682-PE, through its executing unit FONDE...

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Detalles Bibliográficos
Autores: Mendoza A., Cuno A., Condori-Fernandez N., Lovón W.R.
Formato: objeto de conferencia
Fecha de Publicación:2021
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/2966
Enlace del recurso:https://hdl.handle.net/20.500.12390/2966
https://doi.org/10.1007/978-3-030-76228-5_7
Nivel de acceso:acceso abierto
Materia:Reference requirements
Assessment
Physiological datasets
https://purl.org/pe-repo/ocde/ford#2.02.04
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network_acronym_str CONC
network_name_str CONCYTEC-Institucional
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dc.title.none.fl_str_mv An Evaluation of Physiological Public Datasets for Emotion Recognition Systems
title An Evaluation of Physiological Public Datasets for Emotion Recognition Systems
spellingShingle An Evaluation of Physiological Public Datasets for Emotion Recognition Systems
Mendoza A.
Reference requirements
Assessment
Physiological datasets
https://purl.org/pe-repo/ocde/ford#2.02.04
title_short An Evaluation of Physiological Public Datasets for Emotion Recognition Systems
title_full An Evaluation of Physiological Public Datasets for Emotion Recognition Systems
title_fullStr An Evaluation of Physiological Public Datasets for Emotion Recognition Systems
title_full_unstemmed An Evaluation of Physiological Public Datasets for Emotion Recognition Systems
title_sort An Evaluation of Physiological Public Datasets for Emotion Recognition Systems
author Mendoza A.
author_facet Mendoza A.
Cuno A.
Condori-Fernandez N.
Lovón W.R.
author_role author
author2 Cuno A.
Condori-Fernandez N.
Lovón W.R.
author2_role author
author
author
dc.contributor.author.fl_str_mv Mendoza A.
Cuno A.
Condori-Fernandez N.
Lovón W.R.
dc.subject.none.fl_str_mv Reference requirements
topic Reference requirements
Assessment
Physiological datasets
https://purl.org/pe-repo/ocde/ford#2.02.04
dc.subject.es_PE.fl_str_mv Assessment
Physiological datasets
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.02.04
description Acknowledgment. A. Mendoza, A. Cuno, N. Condori-Fernandez and W. Ramos acknowledge financial support from the “Proyecto Concytec - Banco Mundial, Mejo-ramiento y Ampliación de los Servicios del Sistema Nacional de Ciencia Tecnología e Innovación Tecnológica” 8682-PE, through its executing unit FONDECYT [Contract N? 014-2019-FONDECYT-BM-INC.INV]. Also, this work has been partially supported by Datos 4.0 (TIN2016-78011-C4-1-R) funded by MINECO-AEI/FEDER-UE.
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.available.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.issued.fl_str_mv 2021
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12390/2966
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1007/978-3-030-76228-5_7
dc.identifier.scopus.none.fl_str_mv 2-s2.0-85111098913
url https://hdl.handle.net/20.500.12390/2966
https://doi.org/10.1007/978-3-030-76228-5_7
identifier_str_mv 2-s2.0-85111098913
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv Communications in Computer and Information Science
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Science and Business Media Deutschland GmbH
publisher.none.fl_str_mv Springer Science and Business Media Deutschland GmbH
dc.source.none.fl_str_mv reponame:CONCYTEC-Institucional
instname:Consejo Nacional de Ciencia Tecnología e Innovación
instacron:CONCYTEC
instname_str Consejo Nacional de Ciencia Tecnología e Innovación
instacron_str CONCYTEC
institution CONCYTEC
reponame_str CONCYTEC-Institucional
collection CONCYTEC-Institucional
repository.name.fl_str_mv Repositorio Institucional CONCYTEC
repository.mail.fl_str_mv repositorio@concytec.gob.pe
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spelling Publicationrp06241600rp06242600rp02079600rp08400600Mendoza A.Cuno A.Condori-Fernandez N.Lovón W.R.2024-05-30T23:13:38Z2024-05-30T23:13:38Z2021https://hdl.handle.net/20.500.12390/2966https://doi.org/10.1007/978-3-030-76228-5_72-s2.0-85111098913Acknowledgment. A. Mendoza, A. Cuno, N. Condori-Fernandez and W. Ramos acknowledge financial support from the “Proyecto Concytec - Banco Mundial, Mejo-ramiento y Ampliación de los Servicios del Sistema Nacional de Ciencia Tecnología e Innovación Tecnológica” 8682-PE, through its executing unit FONDECYT [Contract N? 014-2019-FONDECYT-BM-INC.INV]. Also, this work has been partially supported by Datos 4.0 (TIN2016-78011-C4-1-R) funded by MINECO-AEI/FEDER-UE.[Background] The performance of emotion recognition systems depends heavily on datasets used in their training, validation, or testing stages. [Aims] This research aims to evaluate the extent to which public available physiological datasets created for emotion recognition systems meet a set of reference requirements. [Method] Firstly, we analyze the applicability of some reference requirements proposed for stress datasets and adjust the corresponding evaluation criteria. Secondly, nine public physiological datasets were identified from a previous survey. [Results] None of the evaluated datasets satisfy all the reference requirements in order to be considered as a reference dataset for being used in the construction of reliable emotion recognition systems. [Conclusion] Although the evaluated datasets do not support the whole reference requirements, they provide a baseline for further development. Also, a greater effort is needed to establish specific reference requirements that can appropriately guide the creation of physiological datasets for emotion recognition systems. © 2021, Springer Nature Switzerland AG.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengSpringer Science and Business Media Deutschland GmbHCommunications in Computer and Information Scienceinfo:eu-repo/semantics/openAccessReference requirementsAssessment-1Physiological datasets-1https://purl.org/pe-repo/ocde/ford#2.02.04-1An Evaluation of Physiological Public Datasets for Emotion Recognition Systemsinfo:eu-repo/semantics/conferenceObjectreponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC20.500.12390/2966oai:repositorio.concytec.gob.pe:20.500.12390/29662024-05-30 16:12:35.837http://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="e5dc2f7d-925b-4ba6-98b8-939e1ce68bda"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>An Evaluation of Physiological Public Datasets for Emotion Recognition Systems</Title> <PublishedIn> <Publication> <Title>Communications in Computer and Information Science</Title> </Publication> </PublishedIn> <PublicationDate>2021</PublicationDate> <DOI>https://doi.org/10.1007/978-3-030-76228-5_7</DOI> <SCP-Number>2-s2.0-85111098913</SCP-Number> <Authors> <Author> <DisplayName>Mendoza A.</DisplayName> <Person id="rp06241" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Cuno A.</DisplayName> <Person id="rp06242" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Condori-Fernandez N.</DisplayName> <Person id="rp02079" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Lovón W.R.</DisplayName> <Person id="rp08400" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Springer Science and Business Media Deutschland GmbH</DisplayName> <OrgUnit /> </Publisher> </Publishers> <Keyword>Reference requirements</Keyword> <Keyword>Assessment</Keyword> <Keyword>Physiological datasets</Keyword> <Abstract>[Background] The performance of emotion recognition systems depends heavily on datasets used in their training, validation, or testing stages. [Aims] This research aims to evaluate the extent to which public available physiological datasets created for emotion recognition systems meet a set of reference requirements. [Method] Firstly, we analyze the applicability of some reference requirements proposed for stress datasets and adjust the corresponding evaluation criteria. Secondly, nine public physiological datasets were identified from a previous survey. [Results] None of the evaluated datasets satisfy all the reference requirements in order to be considered as a reference dataset for being used in the construction of reliable emotion recognition systems. [Conclusion] Although the evaluated datasets do not support the whole reference requirements, they provide a baseline for further development. Also, a greater effort is needed to establish specific reference requirements that can appropriately guide the creation of physiological datasets for emotion recognition systems. © 2021, Springer Nature Switzerland AG.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1
score 13.4481325
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