International Journal of Social Robotics

, Volume 4, Issue 1, pp 29–51

Visuo-auditory Multimodal Emotional Structure to Improve Human-Robot-Interaction

  • José Augusto Prado
  • Carlos Simplício
  • Nicolás F. Lori
  • Jorge Dias
Article

DOI: 10.1007/s12369-011-0134-7

Cite this article as:
Prado, J.A., Simplício, C., Lori, N.F. et al. Int J of Soc Robotics (2012) 4: 29. doi:10.1007/s12369-011-0134-7

Abstract

We propose an approach to analyze and synthesize a set of human facial and vocal expressions, and then use the classified expressions to decide the robot’s response in a human-robot-interaction. During a human-to-human conversation, a person senses the interlocutor’s face and voice, perceives her/his emotional expressions, and processes this information in order to decide which response to give. Moreover, observed emotions are taken into account and the response may be aggressive, funny (henceforth meaning humorous) or just neutral according to not only the observed emotions, but also the personality of the person. The purpose of our proposed structure is to endow robots with the capability to model human emotions, and thus several subproblems need to be solved: feature extraction, classification, decision and synthesis. In the proposed approach we integrate two classifiers for emotion recognition from audio and video, and then use a new method for fusion with the social behavior profile. To keep the person engaged in the interaction, after each iterance of analysis, the robot synthesizes human voice with both lips synchronization and facial expressions. The social behavior profile conducts the personality of the robot. The structure and work flow of the synthesis and decision are addressed, and the Bayesian networks are discussed. We also studied how to analyze and synthesize the emotion from the facial expression and vocal expression. A new probabilistic structure that enables a higher level of interaction between a human and a robot is proposed.

Keywords

Visual perception Auditory perception Emotion recognition Multimodal interaction Social behavior profile Bayesian networks 

Copyright information

© Springer Science & Business Media BV 2011

Authors and Affiliations

  • José Augusto Prado
    • 1
  • Carlos Simplício
    • 1
    • 2
  • Nicolás F. Lori
    • 3
  • Jorge Dias
    • 1
  1. 1.Institute of Systems and RoboticsUniversity of CoimbraCoimbraPortugal
  2. 2.Institute Polytechnic of LeiriaLeiriaPortugal
  3. 3.Institute of Biomedical Research in Light and Image (IBILI), Faculty of MedicineUniversity of CoimbraCoimbraPortugal

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