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The paper presents the study and the performance results of a system for emotion classification using the architecture of a Distributed Speech Recognition System (DSR). The parameters used were extracted by the front-end ETSI Aurora eXtended of a mobile terminal in compliance with the ETSI ES 202 211 V1.1.1 standard. On the basis of the time trend of these parameters, over 3800 statistical parameters...
A stress detection system is developed based on the physiological signals monitored by non-invasive and non-intrusive sensors. The development of this emotion recognition system involved three stages: experiment setup for physiological sensing, signal preprocessing for the extraction of affective features and affective recognition using a learning system. Four signals: galvanic skin response (GSR),...
A stress detection system is developed based on the physiological signals monitored by non-invasive and non-intrusive sensors. The development of this emotion recognition system involved three stages: experiment setup for physiological sensing, signal preprocessing for the extraction of affective features and affective recognition using a learning system. Four signals: galvanic skin response (GSR),...
This paper presents an approach to recognising the gender and expression of face images by means of active appearance models (AAM). Features extracted by a trained AAM are used to construct support vector machine (SVM) classifiers for 4 elementary emotional states (happy, angry, sad, neutral). These classifiers are arranged into a cascade structure in order to optimise overall recognition performance...
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