Integrating Emotion Recognition Tools for Developing Emotionally Intelligent Agents

  1. Marcos-Pablos, Samuel
  2. Lobato, Fernando
  3. García-Peñalvo, Francisco
Revista:
International Journal of Interactive Multimedia and Artificial Intelligence

ISSN: 1989-1660

Año de publicación: 2022

Volumen: 7

Número: 6

Páginas: 69-76

Tipo: Artículo

DOI: 10.9781/IJIMAI.2022.09.004 GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: International Journal of Interactive Multimedia and Artificial Intelligence

Indicadores

Citas recibidas

  • Citas en Scopus: 2 (07-02-2024)
  • Citas en Web of Science: 1 (15-10-2023)
  • Citas en Dimensions: 2 (14-01-2024)

JCR (Journal Impact Factor)

  • Año 2022
  • Factor de impacto de la revista: 3.6
  • Factor de impacto sin autocitas: 3.2
  • Article influence score: 0.473
  • Cuartil mayor: Q3
  • Área: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Cuartil: Q3 Posición en el área: 73/145 (Edicion: SCIE)
  • Área: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Cuartil: Q3 Posición en el área: 56/110 (Edicion: SCIE)

SCImago Journal Rank

  • Año 2022
  • Impacto SJR de la revista: 0.58
  • Cuartil mayor: Q2
  • Área: Computer Networks and Communications Cuartil: Q2 Posición en el área: 147/373
  • Área: Computer Vision and Pattern Recognition Cuartil: Q2 Posición en el área: 42/100
  • Área: Signal Processing Cuartil: Q2 Posición en el área: 52/115
  • Área: Computer Science Applications Cuartil: Q2 Posición en el área: 336/782
  • Área: Statistics and Probability Cuartil: Q2 Posición en el área: 112/258
  • Área: Artificial Intelligence Cuartil: Q3 Posición en el área: 144/284

Scopus CiteScore

  • Año 2022
  • CiteScore de la revista: 2.1
  • Área: Statistics and Probability Percentil: 55
  • Área: Computer Science Applications Percentil: 34
  • Área: Computer Vision and Pattern Recognition Percentil: 34
  • Área: Computer Networks and Communications Percentil: 33
  • Área: Signal Processing Percentil: 31
  • Área: Artificial Intelligence Percentil: 27

Journal Citation Indicator (JCI)

  • Año 2022
  • JCI de la revista: 0.75
  • Cuartil mayor: Q2
  • Área: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Cuartil: Q2 Posición en el área: 72/163
  • Área: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Cuartil: Q2 Posición en el área: 73/192

Dimensions

(Datos actualizados a fecha de 14-01-2024)
  • Citas totales: 2
  • Citas recientes (2 años): 2
  • Field Citation Ratio (FCR): 1.87

Resumen

Emotionally responsive agents that can simulate emotional intelligence increase the acceptance of users towardsthem, as the feeling of empathy reduces negative perceptual feedback. This has fostered research on emotionalintelligence during last decades, and nowadays numerous cloud and local tools for automatic emotionalrecognition are available, even for inexperienced users. These tools however usually focus on the recognitionof discrete emotions sensed from one communication channel, even though multimodal approaches have beenshown to have advantages over unimodal approaches. Therefore, the objective of this paper is to show ourapproach for multimodal emotion recognition using Kalman filters for the fusion of available discrete emotionrecognition tools. The proposed system has been modularly developed based on an evolutionary approach soto be integrated in our digital ecosystems, and new emotional recognition sources can be easily integrated.Obtained results show improvements over unimodal tools when recognizing naturally displayed emotions