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

Ano de publicación: 2022

Volume: 7

Número: 6

Páxinas: 69-76

Tipo: Artigo

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

Outras publicacións 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)

  • Ano 2022
  • Factor de impacto da revista: 3.6
  • Factor de impacto sen autocitas: 3.2
  • Article influence score: 0.473
  • Cuartil maior: Q3
  • Área: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Cuartil: Q3 Posición na área: 73/145 (Edición: SCIE)
  • Área: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Cuartil: Q3 Posición na área: 56/110 (Edición: SCIE)

SCImago Journal Rank

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

Scopus CiteScore

  • Ano 2022
  • CiteScore da 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)

  • Ano 2022
  • JCI da revista: 0.75
  • Cuartil maior: Q2
  • Área: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Cuartil: Q2 Posición na área: 72/163
  • Área: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Cuartil: Q2 Posición na área: 73/192

Dimensions

(Datos actualizados na data de 14-01-2024)
  • Total de citas: 2
  • Citas recentes (2 anos): 2
  • Field Citation Ratio (FCR): 1.87

Resumo

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