By Anton Batliner, Christian Hacker, Stefan Steidl, Elmar Nöth, Jürgen Haas (auth.), Elisabeth André, Laila Dybkjær, Wolfgang Minker, Paul Heisterkamp (eds.)
Human conversational companions are capable, not less than to a definite quantity, to observe the speaker’s or listener’s emotional country and will try to reply to it hence. whilst as an alternative one of many interlocutors is a working laptop or computer a couple of questions come up, corresponding to the next: To what volume are discussion platforms in a position to simulate such behaviors? will we examine the mechanisms of emotional be- viors from looking at and studying the habit of human audio system? How can emotionsbeautomaticallyrecognizedfromauser’smimics,gesturesandspeech? What percentages does a discussion approach need to exhibit feelings itself? And, very importantly, might emotional process habit be fascinating in any respect? Given the kingdom of ongoing study into incorporating feelings in discussion platforms we stumbled on it well timed to arrange an academic and study Workshop on A?ectiveDialogueSystems(ADS2004)atKlosterIrseein GermanyduringJune 14–16, 2004. After profitable ISCA instructional and study Workshops on Multimodal discussion platforms on the related situation in 1999 and 2002, we felt workshop concentrating on the position of a?ect in discussion will be a priceless continuation of the workshop sequence. because of its interdisciplinary nature, the workshop attracted submissions from researchers with very di?erent backgrounds and from many di?erent study components, engaged on, for instance, discussion processing, speech reputation, speech synthesis, embodied conversational brokers, special effects, animation, person modelling, tutoring structures, cognitive structures, and human-computer inter- tion.
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Extra resources for Affective Dialogue Systems: Tutorial and Research Workshop, ADS 2004, Kloster Irsee, Germany, June 14-16, 2004. Proceedings
This research was supported by the Academy of Finland (project number 200 859). Emotions in Short Vowel Segments 23 References 1. : Toward the simulation of emotion in synthetic speech: A review of the literature on human vocal emotion. Journal of Acoustical Society of America 93 (1993) 1097–1108 2. : Communication of verbal modes of expression. Language and Speech 3 (1960) 121–130 3. : Vocal communication of emotion: A review of research paradigms. Speech Communication 40 (2003) 227–256 4. : Speech and Emotional States.
While investigating such an application, one faces several “real world problems” which are determined by environmental inﬂuences. A demo system has been built, in which the feature calculation and the trained classiﬁers are implemented. The system works in push-to-talk mode and is also able to play speech ﬁles and then to classify them. This mode was used to evaluate the environmental conditions. 1 Intensity Intensity contour is an important feature for emotion recognition. Nevertheless, the raw energy contour has the drawback, that it is dependent on several factors, such as the microphone distance, the properties of the microphone and properties of the speaker’s voice.
The processing was performed in the same way as with the basic features of the BVP. In this case however the amplitude ratio was left out. 6 Temperature Temperature was recorded and the common features processed directly from the raw signal. 6 Classification Experiments After having extracted the features as described in the previous section, we then trained a statistical classifier, with the goal of learning the corresponding emotion for a set of features with which it is presented. There are different options for building such a classifier.
Affective Dialogue Systems: Tutorial and Research Workshop, ADS 2004, Kloster Irsee, Germany, June 14-16, 2004. Proceedings by Anton Batliner, Christian Hacker, Stefan Steidl, Elmar Nöth, Jürgen Haas (auth.), Elisabeth André, Laila Dybkjær, Wolfgang Minker, Paul Heisterkamp (eds.)