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A Cognitive Science Reasoning in Recognition of Emotions in Audio -Visual Speech Authors: V. Slavova, W. Verhelst and H. Sahli Publication Year: 2007 Pages: 117-128
Abstract: In this report we summarized the state-of-the-art of speech emotion recognition from the signal processing point of view. On the bases of multi-corporal experiment with machine-learned classifiers, the observation is made that the existing approaches for supervised machine learning lead to database dependent classifiers which can not be applied for multi-language speech emotion recognition without additional training because they discriminate the emotion classes following the used training language. As there are experimental results showing that Humans can perform language independent categorisation, we did a parallel between machine recognition and the cognitive process and tried to discover the sources of these divergent results. The analysis suggests that the main difference is that the speech perception allows extraction of language independent features although the language dependent features are incorporated in all levels of the speech signal and play a strong discriminative function in human perception. Based on several results in related domains, we have supposed that in addition, the cognitive process of emotion-recognition is based on categorisation, assisted by some hierarchical structure of the emotional categories, existing in the cognitive space of all humans. We propose a strategy for developing language independent machine emotion recognition, related to the identification of language independent speech features and to the use of additional information from visual (expression) features. The approach includes emphasizing the structure of the emotion categories in the cognitive space in order to reproduce the human 'strategy' for categorization.
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