A compositionality assembled model for learning and recognizing emotion from bodily expression

Junpei Zhong, Chenguang Yang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

When we are express our internal status, such as emotions, the human body expression we use follows the compositionality principle. It is a theory in linguistic which proposes that the single components of the bodily presentation as well as the rules used to combine them are the major parts to finish this process. In this paper, such principle is applied to the process of expressing and recognizing emotional states through body expression, in which certain key features can be learned to represent certain primitives of the internal emotional state in the form of basic variables. This is done by a hierarchical recurrent neural learning framework (RNN) because of its nonlinear dynamic bifurcation, so that variables can be learned to represent different hierarchies. In addition, we applied some adaptive learning techniques in machine learning for the requirement of real-time emotion recognition, in which a stable representation can be maintained compared to previous work. The model is examined by comparing the PB values between the training and recognition phases. This hierarchical model shows the rationality of the compositionality hypothesis by the RNN learning and explains how key features can be used and combined in bodily expression to show the emotional state.

Original languageEnglish
Title of host publication2019 4th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages821-826
Number of pages6
ISBN (Electronic)9781728100647
DOIs
Publication statusPublished - Jul 2019
Externally publishedYes
Event4th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2019 - Osaka, Japan
Duration: 3 Jul 20195 Jul 2019

Publication series

Name2019 4th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2019

Conference

Conference4th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2019
Country/TerritoryJapan
CityOsaka
Period3/07/195/07/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering
  • Mechanical Engineering
  • Control and Optimization

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