Implementing Emotion Detection from Speech for Psychological Assessment of Elderly People: A Comparative Study of Python- based Approaches and Existing Solutions
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Warnants, I.; Tsiogkas, N.; Roca González, Joaquín Francisco; Ortiz Zaragoza, Francisco José; Méndez, I.; [et al.]Área de conocimiento
Tecnología ElectrónicaPatrocinadores
The HIMTAE project, Robwell subproject (reference RTI2018-095599-A-C22) has been funded by: Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad, en el marco del Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016. The pilot project ADDIM-Poncemar (Asistencia Domiciliaria Digital Integral para Mayores en Poncemar) funded by the "Fundación Integra Digital" of the Region of Murcia is currently being developed in the Day Care Centers of the Poncemar Foundation, in the Health Campus of Lorca, University of Murcia. We thank them for their collaboration and involvement in the testing of the solutions presented in this communication. Finally, we would like to thank the previous CASEIB organising committees for their kindness in allowing us to use their style guides as a reference for this document.Fecha de publicación
2023-11Editorial
Universidad Politécnica de CartagenaCita bibliográfica
WARNANTS, I., et. al. Implementing Emotion Detection from Speech for Psychological Assessment of Elderly People: A Comparative Study of Python- based Approaches and Existing Solutions. En: XLI Congreso Anual de la Sociedad Española de Ingeniería Biomédica. Cartagena: Universidad Politécnica de Cartagena, 2023. Pp. 601-604. ISBN: 978-84-17853-76-1Palabras clave
ADDIM systemPsychological Assessment
Monitoring
Older people's health
Resumen
In the last ten years, the number of people over 65 has increased
30% in Spain. This trend is anticipated to grow and require more
healthcare personnel. To prevent this, people should live longer
independently instead of in care homes. The ADDIM system will
assist them in living independently. The research presented in this
paper is part of the mood detection of the user in the ADDIM
(Asistencia Domiciliaria Digital Integral para Mayores) system.
This is a Digital platform for monitoring older people's health,
safety, companionship, and emotional support at home based on
robotics, artificial intelligence, and ambient assisted living.
To detect user emotions, the right speech corpus, feature
extraction methods, preprocessing methods, and machine
learning models have to be selected. Based on the detected
emotion, the robot will interact with the user to perform
predefined actions. The final mood of the user will be estimated
using this output in conjunction ...
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