Download Affective Dialogue Systems by Andri E. (Ed), Dybkjaer L. (Ed), Minker W. (Ed) PDF

By Andri E. (Ed), Dybkjaer L. (Ed), Minker W. (Ed)

This publication constitutes the refereed court cases of the overseas instructional and study Workshop on Affective discussion platforms, advertisements 2004, held in Kloster Irsee, Germany in June 2004.The 21 revised complete papers and 14 revised brief papers awarded have been rigorously reviewed and chosen for presentation. The papers are equipped in topical sections on emotion popularity; affective consumer modeling; emotional databases, annotation schemes, and instruments; affective conversational brokers and discussion structures; synthesis of emotional speech and facial animations; affective tutoring platforms; assessment of affective discussion structures; and demonstrations.

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We used a combination of these signals, to derive a set of features that can be used to train a neural network classifier. This is then used to automatically detect the emotional state of a user in terms of arousal and valence values, based on the biosignals recorded. 3 The Bio-sensors For measuring the different body functions described in the previous section, we used the sensor set ProComp+ [1]. Their application is depicted in the following Figures. Figure [1] shows the sensors for measuring EMG.

Haag et al. 1 Neural Network Classifier The data for the experiment was gathered from a single subject on different days and different times of the day. Each pattern vector represents a frame of 2 seconds length. The target values that represent valence and arousal were extracted from the IAPS files [2,3], normalised to values between [0,1] and appended to the patterns that were recorded during the presentation of the corresponding picture. The dataset was then divided into three different sets for training, validation and testing.

Alku 21. : A method for generating natural-sounding speech stimuli for cognitive brain research. Clinical Neurophysiology 110 (1999) 1329–1333 22. : Amplitude domain quotient of the glottal volume velocity waveform estimated by inverse filtering. Speech Communication 18 (1996) 131–138 23. , R. E. : Voice source characteristics in six premier country singers. Journal of Voice 13 (1999) 168–183 24. : Some problems in voice source analysis. Speech Communication 13 (1993) 7–22 25. : A comparison of glottal voice source quantification parameters in breathy, normal and pressed phonation of female and male speakers.

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