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Kim, J., André, E., Rehm, M., Vogt, T., & Wagner, J. (2005). Integrating information from speech and physiological signals to achieve emotional sensitivity. Proc. of the 9th European Conference on Speech Communication and Technology. |
publication.Recently, there has been a significant amount of work on the recognition of emotions from speech and biosignals. Most approaches to emotion recognition so far concentrate on a single modality and do not take advantage of the fact that an integrated multimodal analysis may help to resolve ambiguities and compensate for errors. In this paper, we describe various methods for fusing physiological and voice data at the feature-level and the decision-level as well as a hybrid integration scheme. The results of the integrated recognition approach are then compared with the individual recognition results from each modality. we conducted in order to acquire a corpus of spontaneous vocal and physiological data that reveal information on the user's emotional state. We then use the corpus to evaluate the three different fusion methods and compare them with the unimodal recognition approaches. In particular, we are interested in the question of whether a bimodal analysis may indeed improve the accuracy of the recognition results.
CSL Special Issue on Broadening the View on Speaker Analysis
Special Session on BELIEF FUNCTIONS FOR HUMAN BEHAVIOR ANALYSIS AND INTERPRETATION
