Affective Reasoning Based on Bi-modal Interaction and User Stereotypes

This paper describes a novel research approach for affective reasoning that aims at recognizing user emotions within an educational application. The novel approach is based on information about users that arises from two modalities (keyboard and microphone) and is processed based on a combination of the user stereotypes theory and a decision making theory. The resulting system is called Educational Affective Tutor (EAT). EAT is an educational system that helps students learn geography and supports bi-modal interaction. The main focus of this paper is to show how affect recognition is designed based on and empirical study aimed at finding common user reactions that expressed user feelings while they interacted with computers.

[1]  Maria Virvou,et al.  Emotional Intelligence: Constructing User Stereotypes for Affective Bi-modal Interaction , 2006, KES.

[2]  Judy Kay,et al.  Intelligent Tutoring Systems , 2000, Lecture Notes in Computer Science.

[3]  G.A. Tsihrintzis,et al.  Detection and expression classification systems for face images (FADECS) , 2005, IEEE Workshop on Signal Processing Systems Design and Implementation, 2005..

[4]  L. Rothkrantz,et al.  Toward an affect-sensitive multimodal human-computer interaction , 2003, Proc. IEEE.

[5]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[6]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[7]  Tsuyoshi Moriyama,et al.  Measurement of human vocal emotion using fuzzy control , 2001, Systems and Computers in Japan.

[8]  Peter C. Fishburn,et al.  Letter to the Editor - Additive Utilities with Incomplete Product Sets: Application to Priorities and Assignments , 1967, Oper. Res..

[9]  H. Saito,et al.  Evaluation of the relation between emotional concepts and emotional parameters in speech , 2001 .

[10]  Elaine Rich.  Users are individuals: individualizing user models , 1999, Int. J. Hum. Comput. Stud..

[11]  Rosalind W. Picard.  Affective computing: challenges , 2003, Int. J. Hum. Comput. Stud..

[12]  Maria Virvou,et al.  Knowledge Engineering for Affective Bi-Modal Human-Computer Interaction , 2016, SIGMAP.

[13]  Maria Virvou,et al.  Knowledge Engineering Aspects of Affective Bi-Modal Educational Applications , 2007, ICETE.