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Towards a Classifier to Recognize Emotions Using Voice to Improve Recommendations

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Towards a Classifier to Recognize Emotions Using Voice to Improve Recommendations

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dc.contributor.author Fuentes-López, José Manuel es_ES
dc.contributor.author Taverner-Aparicio, Joaquín José es_ES
dc.contributor.author Rincón Arango, Jaime Andrés es_ES
dc.contributor.author Botti Navarro, Vicente Juan es_ES
dc.date.accessioned 2021-12-27T08:37:09Z
dc.date.available 2021-12-27T08:37:09Z
dc.date.issued 2020-10-09 es_ES
dc.identifier.isbn 978-3-030-51999-5 es_ES
dc.identifier.uri http://hdl.handle.net/10251/178898
dc.description.abstract [EN] The recognition of emotions in tone voice is currently a tool with a high potential when it comes to making recommendations, since it allows to personalize recommendations using the mood of the users as information. However, recognizing emotions using tone of voice is a complex task since it is necessary to pre-process the signal and subsequently recognize the emotion. Most of the current proposals use recurrent networks based on sequences with a temporal relationship. The disadvantage of these networks is that they have a high runtime, which makes it difficult to use in real-time applications. On the other hand, when defining this type of classifier, culture and language must be taken into account, since the tone of voice for the same emotion can vary depending on these cultural factors. In this work we propose a culturally adapted model for recognizing emotions from the voice tone using convolutional neural networks. This type of network has a relatively short execution time allowing its use in real time applications. The results we have obtained improve the current state of the art, reaching 93.6% success over the validation set. es_ES
dc.description.sponsorship This work is partially supported by the Spanish Government project TIN2017-89156-R, GVA-CEICE project PROMETEO/2018/002, Generalitat Valenciana and European Social Fund FPI grant ACIF/2017/085, Universitat Politecnica de Valencia research grant (PAID-10-19), and by the Spanish Government (RTI2018-095390-B-C31). es_ES
dc.language Inglés es_ES
dc.publisher Springer es_ES
dc.relation.ispartof Highlights in Practical Applications of Agents, Multi-Agent Systems, and Trust-worthiness. The PAAMS Collection es_ES
dc.relation.ispartofseries Communications in Computer and Information Science;1233 es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Emotion recognition es_ES
dc.subject Voice analysis es_ES
dc.subject Recommendation system es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Towards a Classifier to Recognize Emotions Using Voice to Improve Recommendations es_ES
dc.type Comunicación en congreso es_ES
dc.type Capítulo de libro es_ES
dc.identifier.doi 10.1007/978-3-030-51999-5_18 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-89156-R/ES/AGENTES INTELIGENTES PARA ASESORAR EN PRIVACIDAD EN REDES SOCIALES/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement///ACIF%2F2017%2F085//AYUDA PREDOCTORAL CONSELLERIA-TAVERNER APARICIO/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095390-B-C31/ES/HACIA UNA MOVILIDAD INTELIGENTE Y SOSTENIBLE SOPORTADA POR SISTEMAS MULTI-AGENTES Y EDGE COMPUTING/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement///PROMETEO%2F2018%2F002//TECNOLOGIES PER ORGANITZACIONS HUMANES EMOCIONALS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UPV-VIN//PAID-10-19//Redes de sensores inteligentes en el entorno de las Smart Cities./ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Fuentes-López, JM.; Taverner-Aparicio, JJ.; Rincón Arango, JA.; Botti Navarro, VJ. (2020). Towards a Classifier to Recognize Emotions Using Voice to Improve Recommendations. Springer. 218-225. https://doi.org/10.1007/978-3-030-51999-5_18 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename 18th International Conference on Practical Applications of Agents and Multiagent Systems (PAAMS 2020). Workshops es_ES
dc.relation.conferencedate Octubre 07-09,2020 es_ES
dc.relation.conferenceplace L'Aquila, Italy es_ES
dc.relation.publisherversion https://doi.org/10.1007/978-3-030-51999-5_18 es_ES
dc.description.upvformatpinicio 218 es_ES
dc.description.upvformatpfin 225 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela S\415772 es_ES
dc.contributor.funder European Social Fund es_ES
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