Integrating Emotion Recognition Tools for Developing Emotionally Intelligent Agents

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

ISSN: 1989-1660

Year of publication: 2022

Volume: 7

Issue: 6

Pages: 69-76

Type: Article

DOI: 10.9781/IJIMAI.2022.09.004 GOOGLE SCHOLAR lock_openOpen access editor

More publications in: International Journal of Interactive Multimedia and Artificial Intelligence

Metrics

Cited by

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

JCR (Journal Impact Factor)

  • Year 2022
  • Journal Impact Factor: 3.6
  • Journal Impact Factor without self cites: 3.2
  • Article influence score: 0.473
  • Best Quartile: Q3
  • Area: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Quartile: Q3 Rank in area: 73/145 (Ranking edition: SCIE)
  • Area: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Quartile: Q3 Rank in area: 56/110 (Ranking edition: SCIE)

SCImago Journal Rank

  • Year 2022
  • SJR Journal Impact: 0.58
  • Best Quartile: Q2
  • Area: Computer Networks and Communications Quartile: Q2 Rank in area: 147/373
  • Area: Computer Vision and Pattern Recognition Quartile: Q2 Rank in area: 42/100
  • Area: Signal Processing Quartile: Q2 Rank in area: 52/115
  • Area: Computer Science Applications Quartile: Q2 Rank in area: 336/782
  • Area: Statistics and Probability Quartile: Q2 Rank in area: 112/258
  • Area: Artificial Intelligence Quartile: Q3 Rank in area: 144/284

Scopus CiteScore

  • Year 2022
  • CiteScore of the Journal : 2.1
  • Area: Statistics and Probability Percentile: 55
  • Area: Computer Science Applications Percentile: 34
  • Area: Computer Vision and Pattern Recognition Percentile: 34
  • Area: Computer Networks and Communications Percentile: 33
  • Area: Signal Processing Percentile: 31
  • Area: Artificial Intelligence Percentile: 27

Journal Citation Indicator (JCI)

  • Year 2022
  • Journal Citation Indicator (JCI): 0.75
  • Best Quartile: Q2
  • Area: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Quartile: Q2 Rank in area: 72/163
  • Area: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Quartile: Q2 Rank in area: 73/192

Dimensions

(Data updated as of 14-01-2024)
  • Total citations: 2
  • Recent citations (2 years): 2
  • Field Citation Ratio (FCR): 1.87

Abstract

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