Mohamed Ben Ammar

The Affective Tutoring System

Affective Computing is a new Artificial Intelligence area that deals with the possibility of making computers able to recognize human emotions in different ways. This paper represents a study about the integration of this new area in the intelligent tutoring system. We argue that socially appropriate affective behaviors would provide a new dimension for collaborative learning systems. The main goal is to analyses learner facial expressions and show how Affective Computing could contribute for this interaction, being part of the complete student tracking (traceability) to monitor student behaviors during learning sessions.

The integration of an emotional system in the intelligent system

Summary form only given. In this article, we present a new architecture of the intelligent tutoring system (ITS) and we suggest an original method, which allows recognizing the expression of the learners face during exercise. It helps evaluate his affective state in an emotional system in order to distinguish his influence on his responses. Accordingly, we should first be able to detect his face, extract his important features translating the state of his expression (characteristical features: eyes and mouth,), then we should analyse their configuration and characteristics in order to recognize the expression, which describe and interpret it. Our architecture is based on the observation of the behaviour of the learner; detect engaging signs so as to detect affective responses, which can be the manifestation of feelings of interest, excitement and confusion. From the observation and the identification of the emotional state of the learner, the tutor can undertake actions which influences the quality of learning and its execution (important remarks may reduce the feeling of failure of the learner or avoid the risk of interrupting his work as soon as he feels bored). A scientific and especially emotional analysis is necessary to evaluate and help the learner during exercise.

Towards an intelligent information research system based on the human behavior: Recognition of user emotional state

Our works deals with the problem of Information Retrieval System (IRS) that integrates the human behaviour. This system must be able to recognize the degree of satisfaction of the user of the result found through its facial expression, its physiological state, its gestures and its voice. For this, we propose in this paper an algorithm for recognizing the emotional state of a user during a search session in order to issue the relevant documents that he needs. We present also, the architecture agent of the envisaged system.

A new approach to emotion recognition

In recent years, there has been a growing interest in improving all aspects of the interaction between humans and computers. It is proved that to succeed an intelligent interaction between human and machine, computer must be able to interact naturally as possible, exactly like human-human communication. Humans interact specially with speech, but he can add other way like body gestures and looks, to better display its emotions. Emotions can be expressed by visual, vocal, and other physiological means. In this paper, based on body gestures, we discuss a new intelligent approach to detect user emotion.

A multi-agent based system for affective peer-e-learning

Recent research results indicate that cognitive processes are related to emotions. Since emotions are omnipresent in any kind of interaction it can be advantageous to take them into account, particularly in the context of e-learning. Emotions are now seen as closely related to cognition processes including decision-making, memory, attention, etc. Thus, e-learning environments have begun to take into consideration the emotional state of the learner in order to enhance his performance. This paper presents a tool for man-machine interaction which uses facial input. We believe that facial interaction will have its place among the interaction techniques in the near future. Our work concerns the improvement of computer based learning by mean of a lifelike presence in learning environment. Our approach combines Intelligent Tutoring System with research on human emotion in Cognitive Science, Psychology and Communication. According for relations between emotion, cognition and action in contextual learning, we propose an emotional intelligent tutoring system based on multi-agent architecture to design of adaptive distributed collaborative and peer to peer e-learning environments. An emotionally intelligent tutoring system should be able to provide feedback to students, taking into account relevant aspects of the mental state of the student.

A MULTI-AGENT BASED SYSTEM FOR SENTIMENT ANALYSIS OF USER-GENERATED CONTENT

The recent years have been marked by a rapid growth in the World Wide Web 2.0 applications such as blog posts, forums, mailing lists, and product-review websites. As a result, a special sentiment analysis field has sprung up relevant to the issue of peoples responses to the diversity of available subjects. Hence, one might well wonder: how do people feel and react when dealing with certain topics? In this paper, a new automatic sentiment-processing model has been advanced, whereby the current problems faced by the prevalent existing models can be deciphered and more properly treated. The suggested approach consists in developing a multi-agent system based on a thorough linguistic analysis, meanwhile highlighting the major contributions provided by such a study in combination with the syntactic, semantic, and subjective analyses. Actually, the newly-devised framework enables to resolve the ambiguities and complexities of the natural evaluative language and to strengthen, as well as consolidate, the result...

Real-time learner expressive gestures analysis using in EMASPEL framework

Emotions recognition is a young field, where a growing maturity implies new needs in terms of modelling and integration in the existing models. Based on our previous work (EMASPEL) and expressive gesture analysis; this paper deals with the problem of Emotion Recognition System (ERS); using a camera and no other special tools, we suggest an architecture for an embedded ERS with learner motion analyses detected in a learning framework.

Real-time analysis of non-verbal upper-body expressive gestures

Recently, all aspects of human computer interaction in the multimedia frameworks, try to be adapted with all feedbacks that can be detected from users. This adaptation can take the name of a social dimension. Amongst these feedbacks, the most important and the most credible we find the emotional back. In that topic this paper deals with the problem of Multimedia Emotion Recognition System (MERS). Based on real time analysis, of non verbal upper body expressive gestures; our system try to compute a probability of the emotional state of a user using simple multimedia peripherals.

Real-time affective learner profile analysis using an EMASPEL framework

This paper deals with the problem of Information Retrieval System (IRS) that integrate the user profile that contains novelty dimensions such as psychological state, emotional state, mental state and facial expression. In this paper, we propose an information retrieval system based on human behavior. The architecture of the proposed system is described in details. This IRS will be integrated in EMASPEL E-Learning Framework.