Consistency, Uncertainty or Inconsistency Detection in Multimodal Emotion Recognition

被引:0
|
作者
Fantini, Alessia [1 ,2 ]
Pilato, Giovanni [2 ]
Vitale, Gianpaolo [2 ]
机构
[1] Univ Pisa, Pisa, Italy
[2] CNR, ICAR, Italian Natl Res Council, Palermo, Italy
关键词
Emotion Detection; Mood; Human-Robot Interaction; Inconsistency detection; ARCHITECTURE;
D O I
10.1109/IRC59093.2023.00067
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Humans exploit several sensory channels to recognize emotions and combine the information coming from the different channels into a single perception. Emotion Perception (EP) is also closely related to the Theory of Mind (ToM), which includes processes that capture socially and emotionally related inputs; furthermore, it interprets their meaning and direct responses accordingly. In this paper, we present a first step towards recognizing incoherence in emotions that exploits a three-level cognitive architecture. Starting with multimodal emotion recognition, a decision-maker determines whether a situation of consistency, uncertainty, or inconsistency exists and ultimately attempts to identify which case occurs. The detection is based on a suitable vector representation, in the conceptual level of the architecture, of moods on Russel diagram. A system designed in this way can impact HRI in terms of effectiveness by allowing a robot to get an idea about the actual emotional state of the person it interacts with.
引用
收藏
页码:377 / 380
页数:4
相关论文
共 50 条
  • [1] Multimodal Emotion Recognition With Temporal and Semantic Consistency
    Chen, Bingzhi
    Cao, Qi
    Hou, Mixiao
    Zhang, Zheng
    Lu, Guangming
    Zhang, David
    IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2021, 29 : 3592 - 3603
  • [2] Modeling Hierarchical Uncertainty for Multimodal Emotion Recognition in Conversation
    Chen, Feiyu
    Shao, Jie
    Zhu, Anjie
    Ouyang, Deqiang
    Liu, Xueliang
    Shen, Heng Tao
    IEEE TRANSACTIONS ON CYBERNETICS, 2024, 54 (01) : 187 - 198
  • [3] Uncertainty-Based Learning of a Lightweight Model for Multimodal Emotion Recognition
    Radoi, Anamaria
    Cioroiu, George
    IEEE ACCESS, 2024, 12 : 120362 - 120374
  • [4] Identifying multimodal misinformation leveraging novelty detection and emotion recognition
    Kumari, Rina
    Ashok, Nischal
    Agrawal, Pawan Kumar
    Ghosal, Tirthankar
    Ekbal, Asif
    JOURNAL OF INTELLIGENT INFORMATION SYSTEMS, 2023, 61 (03) : 673 - 694
  • [5] Identifying multimodal misinformation leveraging novelty detection and emotion recognition
    Rina Kumari
    Nischal Ashok
    Pawan Kumar Agrawal
    Tirthankar Ghosal
    Asif Ekbal
    Journal of Intelligent Information Systems, 2023, 61 : 673 - 694
  • [6] Uncertainty in emotion recognition
    Landowska, Agnieszka
    JOURNAL OF INFORMATION COMMUNICATION & ETHICS IN SOCIETY, 2019, 17 (03): : 273 - 291
  • [7] MUSER: MUltimodal Stress Detection using Emotion Recognition as an Auxiliary Task
    Yao, Yiqun
    Papakostas, Michalis
    Burzo, Mihai
    Abouelenien, Mohamed
    Mihalcea, Rada
    2021 CONFERENCE OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: HUMAN LANGUAGE TECHNOLOGIES (NAACL-HLT 2021), 2021, : 2714 - 2725
  • [8] Response to "uncertainty in emotion recognition"
    Gabriels, Katleen
    JOURNAL OF INFORMATION COMMUNICATION & ETHICS IN SOCIETY, 2019, 17 (03): : 295 - 298
  • [9] Responding to uncertainty in emotion recognition
    Schuller, Bjorn
    JOURNAL OF INFORMATION COMMUNICATION & ETHICS IN SOCIETY, 2019, 17 (03): : 299 - 303
  • [10] An Emotion-Space Model of Multimodal Emotion Recognition
    Choe, Kyung-Il
    ADVANCED SCIENCE LETTERS, 2018, 24 (01) : 699 - 702